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Over informative processes, naive estimator of learning—difference between post and pre process scores—underestimates actual learning. A heuristic account for why the naive estimator is negatively biased is as follows: people know as much or more after exposed to an informative process than before it. And the less people know, the larger the number of items they don’t know. And greater the opportunity to guess.
Guessing, even when random, only increases the proportion correct. Thus, bias due to guessing for naive measures of knowledge is always positive. On average, thus, there is more positive bias in the pre-process scores than post-process scores. And naturally, subtracting pre-process scores from post-process provides an attenuated estimate of actual learning. For a more complete treatment of the issue, read this paper by Ken Cor and Gaurav Sood.
We provide a few different ways to adjust estimates of learning for guessing. For now, we limit our attention to cases where the same battery of knowledge questions has been asked in both the pre- and the post-process wave. And to cases where closed-ended questions have been asked. (Guessing is not a serious issue on open-ended items. See more evidence for that in DK Means DK by Robert Luskin and John Bullock.) More generally, the package implements the methods to adjust learning for guessing discussed in this paper.
Proportion of people who learned a particular piece of information over the course of an informative process.
Measurement of knowledge is fundamentally reactive – we must probe to learn. But probing is not without its problems. For instance, people who don’t know the answer try to triangulate based on the cues in the question itself. For another, people are remarkably averse to confessing to their ignorance. So on a closed ended question, lots of people who don’t know the right answer, guess. Here are some pertinent issues that relate to how we analyze the data:
Dealing with Missing Data
If you assume that the data are missing completely at random, you can simply ignore them. Generally, however, respondents tend to skip items they don’t know. So missing responses on knowledge questions typically indicate ignorance. (Of course, it is important to investigate other potential reasons behind missing data. And we encourage researchers to take all precautions.) In our treatment, however, for simplicity sake, we treat missing as indicators of ignorance.
Dealing with Don’t Know
We now know a little bit about Don’t Know. One generally strategy is to treat Don’t Know responses as ignorance. But research suggests that on average there is approximately 3% hidden knowledge behind Don’t Know responses. See DK Means DK by Robert Luskin and John Bullock. Thus one can also choose to replace Don’t Know responses with .03.
Related Knowledge
People either know a particular piece of information or they don’t. On an open-ended question, they may struggle to remember it but those kinds of concerns don’t apply to closed-ended questions where the task is simply to identify the correct answer. What does on occassion happen on closed-ended questions is that people have related cognitions. So for instance, asked to identify the prime minister of France, the respondents sometimes know that one of the options is the king of Sudan and may guess randomly between the remaining options. But that isn’t the same as knowing the prime minister of France.
The standard correction for guessing assumes that people guess randomly. And that people either know or don’t know. Using this assumption, it then uses total number of incorrect answers to estimate the total number of items that the person guessed on. For instance, let us assume there are 4 options on a multiple choice question. Say we have data from 100 respondents. Say there are 70 incorrect answers and 30 correct. Incorrect answers reflect attempts of guessing. (We also assume that people aren’t misinformed.) This means we can triangulat the total number of questions respondents guessed on – 70*(4/3). This means that the proportion of people who know the piece of information is roughly .067. Do it for the pre and the post wave and you have estimate of learning adjusted for guessing using the standard correction.
To get the current development version from github:
# install.packages("devtools")
library(devtools)
#devtools::install_github("soodoku/guess")To adjust estimates of learning for standard correction of guessing, use stndcor. The function requires takes pre test and post test data frames containing responses to the items on the pre- and the post-test, and a lucky vector that contains the probability of getting an item correct when guessing randomly. Under standard guessing correction, it is taken to be inverse of total number of options.
Structure of the Input Data:
Don't know, code all Don't Know responses as ‘d’.# Load library
library(guess)
# Generate some data without DK
pre_test <- data.frame(item1=c(1,0,0,1,0), item2=c(1,NA,0,1,0))
pst_test <- pre_test + cbind(c(0,1,1,0,0), c(0,1,0,0,1))
lucky <- rep(.25, 2)
# Unadjusted Effect
# Treating Don't Know as ignorance
colMeans(nona(pst_test) - nona(pre_test))## item1 item2
## 0.4 0.2# MCAR
colMeans(pst_test - pre_test, na.rm=T)## item1 item2
## 0.40 0.25# Adjusted Effect
stndcor(pre_test, pst_test, lucky)## $pre
## item1 item2
## 0.2000000 0.2666667
##
## $pst
## item1 item2
## 0.7333333 0.5333333
##
## $learn
## item1 item2
## 0.5333333 0.2666667# Without Don't Know
pre_test_var <- c(1,0,0,1,0,1,0)
pst_test_var <- c(1,0,1,1,0,1,1)
print(transmat(pre_test_var, pst_test_var))## x00 x01 x10 x11
## 2 2 0 3# With Don't Know
pre_test_var <- c(1,0,NA,1,"d","d",0,1,0)
pst_test_var <- c(1,0,1,"d",1,0,1,1,"d")
print(transmat(pre_test_var, pst_test_var))## x00 x01 x0d x10 x11 x1d xd0 xd1 xdd
## 1 2 1 0 2 1 1 1 0# load(system.file("data/alldat.rda", package = "guess"))
load("../data/alldat.rda")
# nitems
nitems <- length(alldat)/400
# Vectors of Names
t1 <- paste0("guess.t1", 1:nitems)
t2 <- paste0("guess.t2", 1:nitems)
transmatrix <- multi_transmat(alldat[,t1], alldat[,t2])
res <- guesstimate(transmatrix)##
## Iter: 1 fn: 134.6419 Pars: 0.07656179909 0.00000002922 0.92343817140 0.54285573349
## Iter: 2 fn: 134.6419 Pars: 0.076564035243 0.000000009896 0.923435954861 0.542859555980
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 150.0954 Pars: 0.05000 0.02000 0.93000 0.20000
## Iter: 2 fn: 150.0954 Pars: 0.05000 0.02000 0.93000 0.20000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 100.8425 Pars: 0.04000 0.01600 0.94400 0.49999
## Iter: 2 fn: 100.8425 Pars: 0.04000 0.01600 0.94400 0.50000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 81.2853 Pars: 0.03600 0.03000 0.93400 0.66667
## Iter: 2 fn: 81.2853 Pars: 0.03600 0.03000 0.93400 0.66667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 128.2764 Pars: 0.04114 0.03086 0.92800 0.41667
## Iter: 2 fn: 128.2764 Pars: 0.04114 0.03086 0.92800 0.41667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 131.8840 Pars: 0.04247 0.01565 0.94188 0.10525
## Iter: 2 fn: 131.8840 Pars: 0.04247 0.01565 0.94188 0.10527
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 128.2272 Pars: 0.03756 0.02600 0.93644 0.30770
## Iter: 2 fn: 128.2272 Pars: 0.03756 0.02600 0.93644 0.30769
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 168.8418 Pars: 0.05290 0.02760 0.91950 0.13045
## Iter: 2 fn: 168.8418 Pars: 0.05290 0.02760 0.91950 0.13043
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 178.7014 Pars: 0.05694 0.03365 0.90941 0.22727
## Iter: 2 fn: 178.7014 Pars: 0.05694 0.03365 0.90941 0.22727
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 179.6872 Pars: 0.05408 0.03328 0.91264 0.03845
## Iter: 2 fn: 179.6872 Pars: 0.05408 0.03328 0.91264 0.03846
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1415.6458 Pars: 0.04587 0.02159 0.93254 0.25882
## Iter: 2 fn: 1415.6458 Pars: 0.04587 0.02159 0.93254 0.25882
## solnp--> Completed in 2 iterationsround(res$param.lca[,1:4], 3)## [,1] [,2] [,3] [,4]
## lgg 0.077 0.05 0.040 0.036
## lgk 0.000 0.02 0.016 0.030
## lkk 0.923 0.93 0.944 0.934
## gamma 0.543 0.20 0.500 0.667round(res$est.learning[1:4], 3)## [1] 0.000 0.020 0.016 0.030# Guesstimate with DK
# load(system.file("data/alldat_dk.rda", package = "guess"))
load("../data/alldat_dk.rda")
transmatrix <- multi_transmat(alldat_dk[,t1], alldat_dk[,t2], force9=T)
res_dk <- guesstimate(transmatrix)##
## Iter: 1 fn: 134.6419 Pars: 0.076562252326 0.000000214880 0.000000002369 0.923437523376 0.000000002367 0.000000002367 0.000000002369 0.542856534002
## Iter: 2 fn: 134.6419 Pars: 0.0765622744671 0.0000001894393 0.0000000003812 0.9234375345713 0.0000000003799 0.0000000003799 0.0000000003812 0.5428564920787
## Iter: 3 fn: 134.6419 Pars: 0.0765622761271 0.0000001877334 0.0000000002490 0.9234375351460 0.0000000002477 0.0000000002477 0.0000000002490 0.5428564818674
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 150.0954 Pars: 0.0499999606403 0.0199999635144 0.0000000001635 0.9300000752424 0.0000000001641 0.0000000001641 0.0000000001638 0.1999998619850
## Iter: 2 fn: 150.0954 Pars: 5.000e-02 2.000e-02 4.823e-11 9.300e-01 4.889e-11 4.889e-11 4.861e-11 2.000e-01
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 100.8425 Pars: 0.039999495190 0.015999963656 0.000000007825 0.944000509625 0.000000007967 0.000000007967 0.000000007823 0.499997028567
## Iter: 2 fn: 100.8425 Pars: 0.0399999036867 0.0159999766571 0.0000000007674 0.9440001164614 0.0000000008304 0.0000000008304 0.0000000007666 0.4999991977046
## Iter: 3 fn: 100.8425 Pars: 0.0399999053152 0.0159999767258 0.0000000002108 0.9440001169994 0.0000000002694 0.0000000002694 0.0000000002100 0.4999992149097
## Iter: 4 fn: 100.8425 Pars: 4.000e-02 1.600e-02 3.826e-11 9.440e-01 9.543e-11 9.543e-11 3.748e-11 5.000e-01
## solnp--> Completed in 4 iterations
##
## Iter: 1 fn: 81.2853 Pars: 3.600e-02 3.000e-02 7.593e-12 9.340e-01 7.618e-12 7.618e-12 7.772e-12 6.667e-01
## Iter: 2 fn: 81.2853 Pars: 3.600e-02 3.000e-02 5.021e-12 9.340e-01 5.045e-12 5.045e-12 5.200e-12 6.667e-01
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 128.2764 Pars: 0.041142771823 0.030857105168 0.000000002388 0.928000113637 0.000000002323 0.000000002323 0.000000002391 0.416665957602
## Iter: 2 fn: 128.2764 Pars: 0.0411427721306 0.0308571052407 0.0000000003023 0.9280001215177 0.0000000002522 0.0000000002522 0.0000000003044 0.4166659589663
## Iter: 3 fn: 128.2764 Pars: 0.0411427715733 0.0308571049308 0.0000000001650 0.9280001229323 0.0000000001158 0.0000000001158 0.0000000001670 0.4166659551953
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 131.8840 Pars: 0.042470551085 0.015647016225 0.000000002271 0.941882423658 0.000000002271 0.000000002271 0.000000002271 0.105263111226
## Iter: 2 fn: 131.8840 Pars: 0.0424705514907 0.0156470163053 0.0000000002666 0.9418824311377 0.0000000002666 0.0000000002666 0.0000000002666 0.1052631121290
## Iter: 3 fn: 131.8840 Pars: 0.0424705515292 0.0156470163278 0.0000000001336 0.9418824316085 0.0000000001336 0.0000000001336 0.0000000001336 0.1052631119743
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 128.2273 Pars: 0.03755549203 0.02599996372 0.00000001118 0.93644449953 0.00000001121 0.00000001121 0.00000001118 0.30769180979
## Iter: 2 fn: 128.2272 Pars: 0.0375554937072 0.0259999655631 0.0000000001133 0.9364445402695 0.0000000001173 0.0000000001173 0.0000000001122 0.3076918150389
## Iter: 3 fn: 128.2272 Pars: 3.756e-02 2.600e-02 6.863e-11 9.364e-01 7.263e-11 7.263e-11 6.758e-11 3.077e-01
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 168.8418 Pars: 0.0528999584716 0.0275999615252 0.0000000007793 0.9195000769200 0.0000000007879 0.0000000007879 0.0000000007809 0.1304346686963
## Iter: 2 fn: 168.8418 Pars: 0.0528999586042 0.0275999616437 0.0000000004463 0.9195000779488 0.0000000004546 0.0000000004546 0.0000000004479 0.1304346687845
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 178.7014 Pars: 0.0569411277836 0.0336470251744 0.0000000005190 0.9094118450339 0.0000000005122 0.0000000005122 0.0000000005172 0.2272725082730
## Iter: 2 fn: 178.7014 Pars: 0.0569411280763 0.0336470251668 0.0000000002148 0.9094118459123 0.0000000002083 0.0000000002083 0.0000000002131 0.2272725114672
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 179.6872 Pars: 5.408e-02 3.328e-02 4.054e-11 9.126e-01 4.313e-11 4.313e-11 4.125e-11 3.846e-02
## Iter: 2 fn: 179.6872 Pars: 5.408e-02 3.328e-02 8.979e-12 9.126e-01 1.156e-11 1.156e-11 9.684e-12 3.846e-02
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1415.6461 Pars: 0.04587296618 0.02158726744 0.00000001089 0.93253972283 0.00000001091 0.00000001091 0.00000001090 0.25882326898
## Iter: 2 fn: 1415.6459 Pars: 0.0458729682871 0.0215872683764 0.0000000007563 0.9325397603040 0.0000000007589 0.0000000007589 0.0000000007585 0.2588232714950
## Iter: 3 fn: 1415.6458 Pars: 0.0458729684759 0.0215872681847 0.0000000003604 0.9325397618910 0.0000000003628 0.0000000003628 0.0000000003624 0.2588232755429
## solnp--> Completed in 3 iterationsround(res_dk$param.lca[,1:4], 3)## [,1] [,2] [,3] [,4]
## lgg 0.077 0.05 0.040 0.036
## lgk 0.000 0.02 0.016 0.030
## lgc 0.000 0.00 0.000 0.000
## lkk 0.923 0.93 0.944 0.934
## lcg 0.000 0.00 0.000 0.000
## lck 0.000 0.00 0.000 0.000
## lcc 0.000 0.00 0.000 0.000
## gamma 0.543 0.20 0.500 0.667round(res_dk$est.learning[1:4], 3)## [1] 0.000 0.020 0.016 0.030# Raw
# Generate some data without DK
pre_test <- data.frame(item1=c(1,0,0,1,0), item2=c(1,NA,0,1,0))
pst_test <- pre_test + cbind(c(0,1,1,0,0), c(0,1,0,0,1))
diff <- pst_test - pre_test
stnd_err <- sapply(diff, function(x) sqrt(var(x, na.rm=T)/(length(x)-1)))
# Bootstrapped s.e.
# LCA model
lca_stnd_err <- guess_stnderr(alldat[,t1], alldat[,t2], 10)## [1] 1
##
## Iter: 1 fn: 105.3595 Pars: 0.046722577160 0.000000007789 0.953277414759 0.379314763477
## Iter: 2 fn: 105.3595 Pars: 0.046721728967 0.000000004953 0.953278266080 0.379305162713
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 158.6721 Pars: 0.05095 0.02316 0.92589 0.13636
## Iter: 2 fn: 158.6721 Pars: 0.05095 0.02316 0.92589 0.13636
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 81.2853 Pars: 0.03600 0.03000 0.93400 0.66667
## Iter: 2 fn: 81.2853 Pars: 0.03600 0.03000 0.93400 0.66667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 87.5072 Pars: 0.054001 0.005998 0.940001 0.666678
## Iter: 2 fn: 87.5072 Pars: 0.05400 0.00600 0.94000 0.66667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 121.5056 Pars: 0.04225 0.01950 0.93825 0.38463
## Iter: 2 fn: 121.5056 Pars: 0.04225 0.01950 0.93825 0.38461
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 126.1123 Pars: 0.03812 0.01694 0.94494 0.05555
## Iter: 2 fn: 126.1123 Pars: 0.03812 0.01694 0.94494 0.05556
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 135.1800 Pars: 0.04114 0.03772 0.92114 0.41662
## Iter: 2 fn: 135.1800 Pars: 0.04114 0.03771 0.92114 0.41667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 189.3189 Pars: 0.06827 0.02560 0.90613 0.06250
## Iter: 2 fn: 189.3189 Pars: 0.06827 0.02560 0.90613 0.06250
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 155.0273 Pars: 0.05120 0.03520 0.91360 0.37500
## Iter: 2 fn: 155.0273 Pars: 0.05120 0.03520 0.91360 0.37500
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 182.5722 Pars: 0.05608 0.03323 0.91069 0.03705
## Iter: 2 fn: 182.5722 Pars: 0.05608 0.03323 0.91069 0.03704
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1390.1695 Pars: 0.04517 0.01969 0.93514 0.23838
## Iter: 2 fn: 1390.1695 Pars: 0.04517 0.01969 0.93514 0.23837
## solnp--> Completed in 2 iterations
## [1] 2
##
## Iter: 1 fn: 130.7062 Pars: 0.0722518775 0.0000001279 0.9277479943 0.5294248039
## Iter: 2 fn: 130.7062 Pars: 0.07224990984 0.00000001749 0.92775007267 0.52941139466
## Iter: 3 fn: 130.7062 Pars: 0.072249918660 0.000000001945 0.927750079395 0.529411409792
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 154.0044 Pars: 0.04050 0.03150 0.92800 0.11111
## Iter: 2 fn: 154.0044 Pars: 0.04050 0.03150 0.92800 0.11111
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 73.0666 Pars: 0.03600 0.01800 0.94600 0.66667
## Iter: 2 fn: 73.0666 Pars: 0.03600 0.01800 0.94600 0.66666
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 89.0849 Pars: 0.1620727635 0.0000009363 0.8379262999 0.8889460210
## Iter: 2 fn: 89.0849 Pars: 0.1619965935 0.0000007011 0.8380027054 0.8888886383
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 118.2376 Pars: 0.049999 0.006667 0.943334 0.399998
## Iter: 2 fn: 118.2376 Pars: 0.050000 0.006667 0.943333 0.400000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 123.7286 Pars: 0.02817 0.02600 0.94583 0.07692
## Iter: 2 fn: 123.7286 Pars: 0.02817 0.02600 0.94583 0.07692
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 135.2690 Pars: 0.03756 0.03178 0.93067 0.30768
## Iter: 2 fn: 135.2690 Pars: 0.03756 0.03178 0.93067 0.30769
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 156.1165 Pars: 0.05038 0.02190 0.92771 0.08695
## Iter: 2 fn: 156.1165 Pars: 0.05038 0.02190 0.92771 0.08696
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 189.3867 Pars: 0.08577 0.01588 0.89835 0.37038
## Iter: 2 fn: 189.3867 Pars: 0.08576 0.01588 0.89835 0.37037
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 166.9102 Pars: 0.04399995993 0.03599995479 0.92000008499 0.00000007538
## Iter: 2 fn: 166.9102 Pars: 0.04399995816 0.03599995511 0.92000008673 0.00000003559
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1382.9524 Pars: 0.04654 0.02003 0.93344 0.29091
## Iter: 2 fn: 1382.9524 Pars: 0.04654 0.02003 0.93344 0.29091
## solnp--> Completed in 2 iterations
## [1] 3
##
## Iter: 1 fn: 121.0777 Pars: 0.05760 0.02400 0.91840 0.58333
## Iter: 2 fn: 121.0777 Pars: 0.05760 0.02400 0.91840 0.58333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 155.4906 Pars: 0.05236 0.01964 0.92800 0.08333
## Iter: 2 fn: 155.4906 Pars: 0.05236 0.01964 0.92800 0.08333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 79.4208 Pars: 0.02420 0.00660 0.96920 0.09091
## Iter: 2 fn: 79.4208 Pars: 0.02420 0.00660 0.96920 0.09091
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 90.4891 Pars: 0.03267 0.02801 0.93932 0.57152
## Iter: 2 fn: 90.4891 Pars: 0.03267 0.02800 0.93933 0.57145
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 126.4468 Pars: 0.05625 0.01125 0.93250 0.46667
## Iter: 2 fn: 126.4468 Pars: 0.05625 0.01125 0.93250 0.46667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 122.7553 Pars: 0.03612 0.01700 0.94688 0.05880
## Iter: 2 fn: 122.7553 Pars: 0.03613 0.01700 0.94687 0.05883
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 122.8513 Pars: 0.03025 0.03025 0.93950 0.27272
## Iter: 2 fn: 122.8513 Pars: 0.03025 0.03025 0.93950 0.27273
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 169.0715 Pars: 0.05095 0.03011 0.91895 0.13636
## Iter: 2 fn: 169.0715 Pars: 0.05095 0.03011 0.91895 0.13636
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 142.3149 Pars: 0.02880 0.04080 0.93040 0.16667
## Iter: 2 fn: 142.3149 Pars: 0.02880 0.04080 0.93040 0.16667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 170.2204 Pars: 0.039999967 0.041999957 0.918000075 0.000000283
## Iter: 2 fn: 170.2204 Pars: 0.0399999623 0.0419999567 0.9180000810 0.0000001543
## Iter: 3 fn: 170.2204 Pars: 0.03999995724 0.04199995640 0.91800008636 0.00000002973
## Iter: 4 fn: 170.2204 Pars: 0.039999956124 0.041999956264 0.918000087612 0.000000003726
## solnp--> Completed in 4 iterations
##
## Iter: 1 fn: 1336.7458 Pars: 0.03768 0.02396 0.93836 0.19867
## Iter: 2 fn: 1336.7458 Pars: 0.03769 0.02396 0.93835 0.19868
## solnp--> Completed in 2 iterations
## [1] 4
##
## Iter: 1 fn: 150.0779 Pars: 0.0770416027250 0.0000000005341 0.9229583964483 0.4418602409733
## Iter: 2 fn: 150.0779 Pars: 0.0770416051094 0.0000000001822 0.9229583947081 0.4418602369692
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 125.5305 Pars: 0.04654 0.01163 0.94182 0.31249
## Iter: 2 fn: 125.5305 Pars: 0.04655 0.01164 0.94182 0.31250
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 91.6741 Pars: 0.02700 0.01500 0.95800 0.33333
## Iter: 2 fn: 91.6741 Pars: 0.02700 0.01500 0.95800 0.33333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 76.1239 Pars: 0.07200 0.03601 0.89199 0.83335
## Iter: 2 fn: 76.1239 Pars: 0.07200 0.03600 0.89200 0.83334
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 144.1488 Pars: 0.04655 0.02618 0.92727 0.31250
## Iter: 2 fn: 144.1488 Pars: 0.04655 0.02618 0.92727 0.31250
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 128.5057 Pars: 0.057166618176 0.000000002602 0.942833378930 0.142857098211
## Iter: 2 fn: 128.5057 Pars: 0.0571666209623 0.0000000008003 0.9428333782377 0.1428570621846
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 114.5824 Pars: 0.01829 0.03429 0.94743 0.12500
## Iter: 2 fn: 114.5824 Pars: 0.01829 0.03429 0.94743 0.12500
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 143.7175 Pars: 0.03854 0.02720 0.93427 0.11765
## Iter: 2 fn: 143.7175 Pars: 0.03853 0.02720 0.93427 0.11765
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 192.5972 Pars: 0.06943 0.02828 0.90229 0.22223
## Iter: 2 fn: 192.5972 Pars: 0.06943 0.02829 0.90229 0.22222
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 170.0458 Pars: 0.05208 0.02917 0.91875 0.04000
## Iter: 2 fn: 170.0458 Pars: 0.05208 0.02917 0.91875 0.04000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1381.9339 Pars: 0.04857 0.01619 0.93524 0.27118
## Iter: 2 fn: 1381.9339 Pars: 0.04857 0.01619 0.93524 0.27118
## solnp--> Completed in 2 iterations
## [1] 5
##
## Iter: 1 fn: 149.6656 Pars: 0.067846 0.006462 0.925692 0.380952
## Iter: 2 fn: 149.6656 Pars: 0.067846 0.006462 0.925692 0.380952
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 173.6807 Pars: 0.06945 0.01666 0.91389 0.28001
## Iter: 2 fn: 173.6807 Pars: 0.06944 0.01667 0.91389 0.28000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 87.4491 Pars: 0.03199 0.01601 0.95199 0.50004
## Iter: 2 fn: 87.4491 Pars: 0.03200 0.01600 0.95200 0.49999
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 89.0477 Pars: 0.03600 0.04200 0.92200 0.66666
## Iter: 2 fn: 89.0477 Pars: 0.03600 0.04200 0.92200 0.66667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 108.3869 Pars: 0.03333 0.02333 0.94334 0.40000
## Iter: 2 fn: 108.3869 Pars: 0.03333 0.02333 0.94333 0.40000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 98.9920 Pars: 0.035636 0.005091 0.959273 0.214273
## Iter: 2 fn: 98.9920 Pars: 0.035636 0.005091 0.959273 0.214286
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 118.7326 Pars: 0.02025 0.03375 0.94600 0.11117
## Iter: 2 fn: 118.7326 Pars: 0.02025 0.03375 0.94600 0.11111
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 183.2884 Pars: 0.06145 0.02836 0.91018 0.15385
## Iter: 2 fn: 183.2884 Pars: 0.06145 0.02836 0.91018 0.15385
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 210.4495 Pars: 0.08182 0.03000 0.88818 0.26667
## Iter: 2 fn: 210.4495 Pars: 0.08182 0.03000 0.88818 0.26667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 156.1165 Pars: 0.05038 0.02190 0.92771 0.08695
## Iter: 2 fn: 156.1165 Pars: 0.05038 0.02190 0.92771 0.08696
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1412.9777 Pars: 0.04659 0.02059 0.93283 0.26163
## Iter: 2 fn: 1412.9777 Pars: 0.04659 0.02059 0.93283 0.26163
## solnp--> Completed in 2 iterations
## [1] 6
##
## Iter: 1 fn: 105.6160 Pars: 0.06250072528 0.00000004976 0.93749922467 0.60000285361
## Iter: 2 fn: 105.6160 Pars: 0.062499894608 0.000000002683 0.937500102709 0.599999479155
## Iter: 3 fn: 105.6160 Pars: 0.062499894566 0.000000001559 0.937500103875 0.599999477922
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 162.5757 Pars: 0.04512 0.03325 0.92163 0.15791
## Iter: 2 fn: 162.5757 Pars: 0.04512 0.03325 0.92163 0.15789
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 89.0477 Pars: 0.01800 0.02700 0.95500 0.33333
## Iter: 2 fn: 89.0477 Pars: 0.01800 0.02700 0.95500 0.33333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 89.2923 Pars: 0.03199 0.08801 0.88000 0.75000
## Iter: 2 fn: 89.2923 Pars: 0.03200 0.08800 0.88000 0.75000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 103.4635 Pars: 0.05400 0.03000 0.91599 0.66669
## Iter: 2 fn: 103.4635 Pars: 0.05400 0.03000 0.91600 0.66667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 136.0270 Pars: 0.04266 0.02133 0.93601 0.24998
## Iter: 2 fn: 136.0270 Pars: 0.04267 0.02133 0.93600 0.25000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 121.2452 Pars: 0.05397452 0.00002533 0.94600015 0.33317637
## Iter: 2 fn: 121.2452 Pars: 0.0539994284 0.0000005199 0.9460000517 0.3333299539
## Iter: 3 fn: 121.2452 Pars: 0.0539995393 0.0000004084 0.9460000522 0.3333306245
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 134.9492 Pars: 0.04610 0.01467 0.93924 0.04545
## Iter: 2 fn: 134.9492 Pars: 0.04610 0.01467 0.93924 0.04545
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 169.1859 Pars: 0.04900 0.03267 0.91833 0.14286
## Iter: 2 fn: 169.1859 Pars: 0.04900 0.03267 0.91833 0.14286
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 157.5158 Pars: 0.04609 0.02724 0.92667 0.04546
## Iter: 2 fn: 157.5158 Pars: 0.04610 0.02724 0.92667 0.04545
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1312.1547 Pars: 0.04143 0.02004 0.93853 0.26144
## Iter: 2 fn: 1312.1547 Pars: 0.04143 0.02004 0.93853 0.26144
## solnp--> Completed in 2 iterations
## [1] 7
##
## Iter: 1 fn: 137.7057 Pars: 0.05254 0.01546 0.93200 0.35291
## Iter: 2 fn: 137.7057 Pars: 0.05255 0.01545 0.93200 0.35294
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 132.8261 Pars: 0.03853 0.02040 0.94107 0.11765
## Iter: 2 fn: 132.8261 Pars: 0.03853 0.02040 0.94107 0.11765
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 109.2359 Pars: 0.04840 0.01760 0.93400 0.54545
## Iter: 2 fn: 109.2359 Pars: 0.04840 0.01760 0.93400 0.54545
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 45.5157 Pars: 0.003999955 0.011999960 0.984000085 0.000001027
## Iter: 2 fn: 45.5157 Pars: 0.00399995087 0.01199995234 0.98400009680 0.00000006701
## Iter: 3 fn: 45.5157 Pars: 0.00399995073 0.01199995205 0.98400009722 0.00000003425
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 105.3140 Pars: 0.043555 0.003111 0.953333 0.357141
## Iter: 2 fn: 105.3140 Pars: 0.043556 0.003111 0.953333 0.357143
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 137.9923 Pars: 0.059524 0.002381 0.938095 0.160000
## Iter: 2 fn: 137.9923 Pars: 0.059524 0.002381 0.938095 0.160000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 137.9947 Pars: 0.05689 0.01778 0.92533 0.43750
## Iter: 2 fn: 137.9947 Pars: 0.05689 0.01778 0.92533 0.43750
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 151.8269 Pars: 0.04900 0.02100 0.93000 0.14286
## Iter: 2 fn: 151.8269 Pars: 0.04900 0.02100 0.93000 0.14286
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 181.8365 Pars: 0.04446 0.05493 0.90061 0.23530
## Iter: 2 fn: 181.8365 Pars: 0.04446 0.05492 0.90061 0.23530
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 186.3808 Pars: 0.05208 0.03958 0.90833 0.04000
## Iter: 2 fn: 186.3808 Pars: 0.05208 0.03958 0.90833 0.04000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1368.8204 Pars: 0.04287 0.02079 0.93634 0.23032
## Iter: 2 fn: 1368.8204 Pars: 0.04287 0.02079 0.93634 0.23030
## solnp--> Completed in 2 iterations
## [1] 8
##
## Iter: 1 fn: 138.4520 Pars: 0.0691362976 0.0000001194 0.9308635827 0.4358971394
## Iter: 2 fn: 138.4520 Pars: 0.06913626642 0.00000003935 0.93086369423 0.43589705238
## Iter: 3 fn: 138.4520 Pars: 0.0691363056726 0.0000000001597 0.9308636941681 0.4358972032714
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 139.4971 Pars: 0.04629 0.01800 0.93571 0.22222
## Iter: 2 fn: 139.4971 Pars: 0.04629 0.01800 0.93571 0.22222
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 116.8411 Pars: 0.03600 0.02100 0.94300 0.33332
## Iter: 2 fn: 116.8411 Pars: 0.03600 0.02100 0.94300 0.33333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 77.7518 Pars: 0.04900 0.01400 0.93700 0.71429
## Iter: 2 fn: 77.7518 Pars: 0.04900 0.01400 0.93700 0.71428
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 128.4439 Pars: 0.04800 0.03200 0.92000 0.50000
## Iter: 2 fn: 128.4439 Pars: 0.04800 0.03200 0.92000 0.50000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 120.3604 Pars: 0.04050 0.01125 0.94825 0.11111
## Iter: 2 fn: 120.3604 Pars: 0.04050 0.01125 0.94825 0.11111
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 106.8588 Pars: 0.01633 0.03267 0.95100 0.14279
## Iter: 2 fn: 106.8588 Pars: 0.01633 0.03267 0.95100 0.14286
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 159.1280 Pars: 0.04033 0.07333 0.88633 0.45455
## Iter: 2 fn: 159.1280 Pars: 0.04033 0.07333 0.88633 0.45455
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 189.4939 Pars: 0.06760 0.02860 0.90380 0.23078
## Iter: 2 fn: 189.4939 Pars: 0.06760 0.02860 0.90380 0.23077
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 174.6289 Pars: 0.06031 0.02369 0.91600 0.07143
## Iter: 2 fn: 174.6289 Pars: 0.06031 0.02369 0.91600 0.07143
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1389.8039 Pars: 0.04397 0.02323 0.93281 0.27672
## Iter: 2 fn: 1389.8038 Pars: 0.04397 0.02323 0.93281 0.27673
## solnp--> Completed in 2 iterations
## [1] 9
##
## Iter: 1 fn: 105.0705 Pars: 0.07199982872 0.00000006055 0.92800011044 0.66666604994
## Iter: 2 fn: 105.0705 Pars: 0.07199984310 0.00000001874 0.92800013815 0.66666605337
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 129.9523 Pars: 0.05290 0.00460 0.94250 0.13044
## Iter: 2 fn: 129.9523 Pars: 0.05290 0.00460 0.94250 0.13044
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 94.3171 Pars: 0.02450 0.02800 0.94750 0.42856
## Iter: 2 fn: 94.3171 Pars: 0.02450 0.02800 0.94750 0.42857
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 67.6779 Pars: 0.0845099419486 0.0000000006277 0.9154900571318 0.8461720339470
## Iter: 2 fn: 67.6779 Pars: 0.08449785454 0.00000000032 0.91550214514 0.84615043582
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 142.0349 Pars: 0.03756 0.03756 0.92489 0.30769
## Iter: 2 fn: 142.0349 Pars: 0.03756 0.03756 0.92489 0.30769
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 131.2505 Pars: 0.04813 0.01013 0.94173 0.21052
## Iter: 2 fn: 131.2505 Pars: 0.04813 0.01013 0.94173 0.21053
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 112.3169 Pars: 0.04000 0.02800 0.93200 0.49998
## Iter: 2 fn: 112.3169 Pars: 0.04000 0.02800 0.93200 0.50000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 186.6110 Pars: 0.06145 0.03073 0.90782 0.15385
## Iter: 2 fn: 186.6110 Pars: 0.06145 0.03073 0.90782 0.15385
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 180.2304 Pars: 0.0885963414 0.0000001728 0.9114034854 0.3114817103
## Iter: 2 fn: 180.2303 Pars: 0.08859327043 0.00000004167 0.91140668789 0.31146506929
## Iter: 3 fn: 180.2303 Pars: 0.088598103784 0.000000005886 0.911401890330 0.311490911864
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 182.4494 Pars: 0.0439999677 0.0459999574 0.9100000746 0.0000002526
## Iter: 2 fn: 182.4494 Pars: 0.0439999630 0.0459999571 0.9100000799 0.0000001461
## Iter: 3 fn: 182.4494 Pars: 0.04399995802 0.04599995709 0.91000008489 0.00000003035
## Iter: 4 fn: 182.4494 Pars: 0.043999956688 0.045999956823 0.910000086488 0.000000002915
## solnp--> Completed in 4 iterations
##
## Iter: 1 fn: 1386.4757 Pars: 0.04755 0.01835 0.93410 0.28070
## Iter: 2 fn: 1386.4757 Pars: 0.04755 0.01835 0.93410 0.28070
## solnp--> Completed in 2 iterations
## [1] 10
##
## Iter: 1 fn: 128.4439 Pars: 0.057142802903 0.000000007229 0.942857189576 0.299999831435
## Iter: 2 fn: 128.4439 Pars: 0.057142806076 0.000000001737 0.942857192187 0.299999844731
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 160.6000 Pars: 0.05188 0.02471 0.92341 0.19047
## Iter: 2 fn: 160.6000 Pars: 0.05188 0.02471 0.92341 0.19048
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 100.0937 Pars: 0.04050 0.02250 0.93700 0.55555
## Iter: 2 fn: 100.0937 Pars: 0.04050 0.02250 0.93700 0.55555
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 121.2452 Pars: 0.04800 0.02400 0.92800 0.49998
## Iter: 2 fn: 121.2452 Pars: 0.04800 0.02400 0.92800 0.50000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 118.5063 Pars: 0.06424384 0.00004192 0.93571425 0.53318186
## Iter: 2 fn: 118.5062 Pars: 0.0642847581 0.0000008747 0.9357143672 0.5333297539
## Iter: 3 fn: 118.5062 Pars: 0.0642849366 0.0000006959 0.9357143675 0.5333304101
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 114.0325 Pars: 0.03462 0.01385 0.95154 0.13334
## Iter: 2 fn: 114.0325 Pars: 0.03462 0.01385 0.95154 0.13333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 156.3493 Pars: 0.06453 0.01173 0.92373 0.31818
## Iter: 2 fn: 156.3493 Pars: 0.06453 0.01173 0.92373 0.31818
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 142.8815 Pars: 0.04444 0.02000 0.93556 0.10000
## Iter: 2 fn: 142.8815 Pars: 0.04444 0.02000 0.93556 0.10000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 220.6438 Pars: 0.08736 0.03382 0.87882 0.29033
## Iter: 2 fn: 220.6438 Pars: 0.08736 0.03382 0.87882 0.29032
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 167.0704 Pars: 0.05009 0.02922 0.92069 0.04168
## Iter: 2 fn: 167.0704 Pars: 0.05009 0.02922 0.92070 0.04167
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1461.9631 Pars: 0.05249 0.01704 0.93047 0.27225
## Iter: 2 fn: 1461.9631 Pars: 0.05249 0.01704 0.93047 0.27225
## solnp--> Completed in 2 iterationssapply(lca_stnd_err, function(x) round(head(x, 1),3))## $stnderrs.lca.params
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## lgg 0.01 0.009 0.009 0.043 0.009 0.01 0.017 0.01 0.021 0.006
##
## $avg.effects
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
## lca 0.005 0.02 0.02 0.025 0.019 0.012 0.026 0.029 0.03 0.033 0.02
##
## $stnderrs.effects
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
## lca 0.008 0.009 0.007 0.026 0.013 0.008 0.012 0.016 0.014 0.008 0.002lca_dk_stnd_err <- guess_stnderr(alldat_dk[,t1], alldat_dk[,t2], 10)## [1] 1
##
## Iter: 1 fn: 105.3595 Pars: 0.046722577160 0.000000007789 0.953277414759 0.379314763477
## Iter: 2 fn: 105.3595 Pars: 0.046721728967 0.000000004953 0.953278266080 0.379305162713
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 158.6721 Pars: 0.05095 0.02316 0.92589 0.13636
## Iter: 2 fn: 158.6721 Pars: 0.05095 0.02316 0.92589 0.13636
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 81.2853 Pars: 0.03600 0.03000 0.93400 0.66667
## Iter: 2 fn: 81.2853 Pars: 0.03600 0.03000 0.93400 0.66667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 87.5072 Pars: 0.054001 0.005998 0.940001 0.666678
## Iter: 2 fn: 87.5072 Pars: 0.05400 0.00600 0.94000 0.66667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 121.5056 Pars: 0.04225 0.01950 0.93825 0.38463
## Iter: 2 fn: 121.5056 Pars: 0.04225 0.01950 0.93825 0.38461
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 126.1123 Pars: 0.03812 0.01694 0.94494 0.05555
## Iter: 2 fn: 126.1123 Pars: 0.03812 0.01694 0.94494 0.05556
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 135.1800 Pars: 0.04114 0.03772 0.92114 0.41662
## Iter: 2 fn: 135.1800 Pars: 0.04114 0.03771 0.92114 0.41667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 189.3189 Pars: 0.06827 0.02560 0.90613 0.06250
## Iter: 2 fn: 189.3189 Pars: 0.06827 0.02560 0.90613 0.06250
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 155.0273 Pars: 0.05120 0.03520 0.91360 0.37500
## Iter: 2 fn: 155.0273 Pars: 0.05120 0.03520 0.91360 0.37500
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 182.5722 Pars: 0.05608 0.03323 0.91069 0.03705
## Iter: 2 fn: 182.5722 Pars: 0.05608 0.03323 0.91069 0.03704
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1390.1695 Pars: 0.04517 0.01969 0.93514 0.23838
## Iter: 2 fn: 1390.1695 Pars: 0.04517 0.01969 0.93514 0.23837
## solnp--> Completed in 2 iterations
## [1] 2
##
## Iter: 1 fn: 130.7062 Pars: 0.0722518775 0.0000001279 0.9277479943 0.5294248039
## Iter: 2 fn: 130.7062 Pars: 0.07224990984 0.00000001749 0.92775007267 0.52941139466
## Iter: 3 fn: 130.7062 Pars: 0.072249918660 0.000000001945 0.927750079395 0.529411409792
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 154.0044 Pars: 0.04050 0.03150 0.92800 0.11111
## Iter: 2 fn: 154.0044 Pars: 0.04050 0.03150 0.92800 0.11111
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 73.0666 Pars: 0.03600 0.01800 0.94600 0.66667
## Iter: 2 fn: 73.0666 Pars: 0.03600 0.01800 0.94600 0.66666
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 89.0849 Pars: 0.1620727635 0.0000009363 0.8379262999 0.8889460210
## Iter: 2 fn: 89.0849 Pars: 0.1619965935 0.0000007011 0.8380027054 0.8888886383
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 118.2376 Pars: 0.049999 0.006667 0.943334 0.399998
## Iter: 2 fn: 118.2376 Pars: 0.050000 0.006667 0.943333 0.400000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 123.7286 Pars: 0.02817 0.02600 0.94583 0.07692
## Iter: 2 fn: 123.7286 Pars: 0.02817 0.02600 0.94583 0.07692
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 135.2690 Pars: 0.03756 0.03178 0.93067 0.30768
## Iter: 2 fn: 135.2690 Pars: 0.03756 0.03178 0.93067 0.30769
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 156.1165 Pars: 0.05038 0.02190 0.92771 0.08695
## Iter: 2 fn: 156.1165 Pars: 0.05038 0.02190 0.92771 0.08696
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 189.3867 Pars: 0.08577 0.01588 0.89835 0.37038
## Iter: 2 fn: 189.3867 Pars: 0.08576 0.01588 0.89835 0.37037
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 166.9102 Pars: 0.04399995993 0.03599995479 0.92000008499 0.00000007538
## Iter: 2 fn: 166.9102 Pars: 0.04399995816 0.03599995511 0.92000008673 0.00000003559
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1382.9524 Pars: 0.04654 0.02003 0.93344 0.29091
## Iter: 2 fn: 1382.9524 Pars: 0.04654 0.02003 0.93344 0.29091
## solnp--> Completed in 2 iterations
## [1] 3
##
## Iter: 1 fn: 121.0777 Pars: 0.05760 0.02400 0.91840 0.58333
## Iter: 2 fn: 121.0777 Pars: 0.05760 0.02400 0.91840 0.58333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 155.4906 Pars: 0.05236 0.01964 0.92800 0.08333
## Iter: 2 fn: 155.4906 Pars: 0.05236 0.01964 0.92800 0.08333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 79.4208 Pars: 0.02420 0.00660 0.96920 0.09091
## Iter: 2 fn: 79.4208 Pars: 0.02420 0.00660 0.96920 0.09091
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 90.4891 Pars: 0.03267 0.02801 0.93932 0.57152
## Iter: 2 fn: 90.4891 Pars: 0.03267 0.02800 0.93933 0.57145
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 126.4468 Pars: 0.05625 0.01125 0.93250 0.46667
## Iter: 2 fn: 126.4468 Pars: 0.05625 0.01125 0.93250 0.46667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 122.7553 Pars: 0.03612 0.01700 0.94688 0.05880
## Iter: 2 fn: 122.7553 Pars: 0.03613 0.01700 0.94687 0.05883
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 122.8513 Pars: 0.03025 0.03025 0.93950 0.27272
## Iter: 2 fn: 122.8513 Pars: 0.03025 0.03025 0.93950 0.27273
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 169.0715 Pars: 0.05095 0.03011 0.91895 0.13636
## Iter: 2 fn: 169.0715 Pars: 0.05095 0.03011 0.91895 0.13636
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 142.3149 Pars: 0.02880 0.04080 0.93040 0.16667
## Iter: 2 fn: 142.3149 Pars: 0.02880 0.04080 0.93040 0.16667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 170.2204 Pars: 0.039999967 0.041999957 0.918000075 0.000000283
## Iter: 2 fn: 170.2204 Pars: 0.0399999623 0.0419999567 0.9180000810 0.0000001543
## Iter: 3 fn: 170.2204 Pars: 0.03999995724 0.04199995640 0.91800008636 0.00000002973
## Iter: 4 fn: 170.2204 Pars: 0.039999956124 0.041999956264 0.918000087612 0.000000003726
## solnp--> Completed in 4 iterations
##
## Iter: 1 fn: 1336.7458 Pars: 0.03768 0.02396 0.93836 0.19867
## Iter: 2 fn: 1336.7458 Pars: 0.03769 0.02396 0.93835 0.19868
## solnp--> Completed in 2 iterations
## [1] 4
##
## Iter: 1 fn: 150.0779 Pars: 0.0770416027250 0.0000000005341 0.9229583964483 0.4418602409733
## Iter: 2 fn: 150.0779 Pars: 0.0770416051094 0.0000000001822 0.9229583947081 0.4418602369692
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 125.5305 Pars: 0.04654 0.01163 0.94182 0.31249
## Iter: 2 fn: 125.5305 Pars: 0.04655 0.01164 0.94182 0.31250
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 91.6741 Pars: 0.02700 0.01500 0.95800 0.33333
## Iter: 2 fn: 91.6741 Pars: 0.02700 0.01500 0.95800 0.33333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 76.1239 Pars: 0.07200 0.03601 0.89199 0.83335
## Iter: 2 fn: 76.1239 Pars: 0.07200 0.03600 0.89200 0.83334
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 144.1488 Pars: 0.04655 0.02618 0.92727 0.31250
## Iter: 2 fn: 144.1488 Pars: 0.04655 0.02618 0.92727 0.31250
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 128.5057 Pars: 0.057166618176 0.000000002602 0.942833378930 0.142857098211
## Iter: 2 fn: 128.5057 Pars: 0.0571666209623 0.0000000008003 0.9428333782377 0.1428570621846
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 114.5824 Pars: 0.01829 0.03429 0.94743 0.12500
## Iter: 2 fn: 114.5824 Pars: 0.01829 0.03429 0.94743 0.12500
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 143.7175 Pars: 0.03854 0.02720 0.93427 0.11765
## Iter: 2 fn: 143.7175 Pars: 0.03853 0.02720 0.93427 0.11765
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 192.5972 Pars: 0.06943 0.02828 0.90229 0.22223
## Iter: 2 fn: 192.5972 Pars: 0.06943 0.02829 0.90229 0.22222
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 170.0458 Pars: 0.05208 0.02917 0.91875 0.04000
## Iter: 2 fn: 170.0458 Pars: 0.05208 0.02917 0.91875 0.04000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1381.9339 Pars: 0.04857 0.01619 0.93524 0.27118
## Iter: 2 fn: 1381.9339 Pars: 0.04857 0.01619 0.93524 0.27118
## solnp--> Completed in 2 iterations
## [1] 5
##
## Iter: 1 fn: 149.6656 Pars: 0.067846 0.006462 0.925692 0.380952
## Iter: 2 fn: 149.6656 Pars: 0.067846 0.006462 0.925692 0.380952
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 173.6807 Pars: 0.06945 0.01666 0.91389 0.28001
## Iter: 2 fn: 173.6807 Pars: 0.06944 0.01667 0.91389 0.28000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 87.4491 Pars: 0.03199 0.01601 0.95199 0.50004
## Iter: 2 fn: 87.4491 Pars: 0.03200 0.01600 0.95200 0.49999
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 89.0477 Pars: 0.03600 0.04200 0.92200 0.66666
## Iter: 2 fn: 89.0477 Pars: 0.03600 0.04200 0.92200 0.66667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 108.3869 Pars: 0.03333 0.02333 0.94334 0.40000
## Iter: 2 fn: 108.3869 Pars: 0.03333 0.02333 0.94333 0.40000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 98.9920 Pars: 0.035636 0.005091 0.959273 0.214273
## Iter: 2 fn: 98.9920 Pars: 0.035636 0.005091 0.959273 0.214286
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 118.7326 Pars: 0.02025 0.03375 0.94600 0.11117
## Iter: 2 fn: 118.7326 Pars: 0.02025 0.03375 0.94600 0.11111
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 183.2884 Pars: 0.06145 0.02836 0.91018 0.15385
## Iter: 2 fn: 183.2884 Pars: 0.06145 0.02836 0.91018 0.15385
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 210.4495 Pars: 0.08182 0.03000 0.88818 0.26667
## Iter: 2 fn: 210.4495 Pars: 0.08182 0.03000 0.88818 0.26667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 156.1165 Pars: 0.05038 0.02190 0.92771 0.08695
## Iter: 2 fn: 156.1165 Pars: 0.05038 0.02190 0.92771 0.08696
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1412.9777 Pars: 0.04659 0.02059 0.93283 0.26163
## Iter: 2 fn: 1412.9777 Pars: 0.04659 0.02059 0.93283 0.26163
## solnp--> Completed in 2 iterations
## [1] 6
##
## Iter: 1 fn: 105.6160 Pars: 0.06250072528 0.00000004976 0.93749922467 0.60000285361
## Iter: 2 fn: 105.6160 Pars: 0.062499894608 0.000000002683 0.937500102709 0.599999479155
## Iter: 3 fn: 105.6160 Pars: 0.062499894566 0.000000001559 0.937500103875 0.599999477922
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 162.5757 Pars: 0.04512 0.03325 0.92163 0.15791
## Iter: 2 fn: 162.5757 Pars: 0.04512 0.03325 0.92163 0.15789
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 89.0477 Pars: 0.01800 0.02700 0.95500 0.33333
## Iter: 2 fn: 89.0477 Pars: 0.01800 0.02700 0.95500 0.33333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 89.2923 Pars: 0.03199 0.08801 0.88000 0.75000
## Iter: 2 fn: 89.2923 Pars: 0.03200 0.08800 0.88000 0.75000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 103.4635 Pars: 0.05400 0.03000 0.91599 0.66669
## Iter: 2 fn: 103.4635 Pars: 0.05400 0.03000 0.91600 0.66667
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 136.0270 Pars: 0.04266 0.02133 0.93601 0.24998
## Iter: 2 fn: 136.0270 Pars: 0.04267 0.02133 0.93600 0.25000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 121.2452 Pars: 0.05397452 0.00002533 0.94600015 0.33317637
## Iter: 2 fn: 121.2452 Pars: 0.0539994284 0.0000005199 0.9460000517 0.3333299539
## Iter: 3 fn: 121.2452 Pars: 0.0539995393 0.0000004084 0.9460000522 0.3333306245
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 134.9492 Pars: 0.04610 0.01467 0.93924 0.04545
## Iter: 2 fn: 134.9492 Pars: 0.04610 0.01467 0.93924 0.04545
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 169.1859 Pars: 0.04900 0.03267 0.91833 0.14286
## Iter: 2 fn: 169.1859 Pars: 0.04900 0.03267 0.91833 0.14286
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 157.5158 Pars: 0.04609 0.02724 0.92667 0.04546
## Iter: 2 fn: 157.5158 Pars: 0.04610 0.02724 0.92667 0.04545
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1312.1547 Pars: 0.04143 0.02004 0.93853 0.26144
## Iter: 2 fn: 1312.1547 Pars: 0.04143 0.02004 0.93853 0.26144
## solnp--> Completed in 2 iterations
## [1] 7
##
## Iter: 1 fn: 137.7057 Pars: 0.05254 0.01546 0.93200 0.35291
## Iter: 2 fn: 137.7057 Pars: 0.05255 0.01545 0.93200 0.35294
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 132.8261 Pars: 0.03853 0.02040 0.94107 0.11765
## Iter: 2 fn: 132.8261 Pars: 0.03853 0.02040 0.94107 0.11765
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 109.2359 Pars: 0.04840 0.01760 0.93400 0.54545
## Iter: 2 fn: 109.2359 Pars: 0.04840 0.01760 0.93400 0.54545
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 45.5157 Pars: 0.003999955 0.011999960 0.984000085 0.000001027
## Iter: 2 fn: 45.5157 Pars: 0.00399995087 0.01199995234 0.98400009680 0.00000006701
## Iter: 3 fn: 45.5157 Pars: 0.00399995073 0.01199995205 0.98400009722 0.00000003425
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 105.3140 Pars: 0.043555 0.003111 0.953333 0.357141
## Iter: 2 fn: 105.3140 Pars: 0.043556 0.003111 0.953333 0.357143
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 137.9923 Pars: 0.059524 0.002381 0.938095 0.160000
## Iter: 2 fn: 137.9923 Pars: 0.059524 0.002381 0.938095 0.160000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 137.9947 Pars: 0.05689 0.01778 0.92533 0.43750
## Iter: 2 fn: 137.9947 Pars: 0.05689 0.01778 0.92533 0.43750
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 151.8269 Pars: 0.04900 0.02100 0.93000 0.14286
## Iter: 2 fn: 151.8269 Pars: 0.04900 0.02100 0.93000 0.14286
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 181.8365 Pars: 0.04446 0.05493 0.90061 0.23530
## Iter: 2 fn: 181.8365 Pars: 0.04446 0.05492 0.90061 0.23530
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 186.3808 Pars: 0.05208 0.03958 0.90833 0.04000
## Iter: 2 fn: 186.3808 Pars: 0.05208 0.03958 0.90833 0.04000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1368.8204 Pars: 0.04287 0.02079 0.93634 0.23032
## Iter: 2 fn: 1368.8204 Pars: 0.04287 0.02079 0.93634 0.23030
## solnp--> Completed in 2 iterations
## [1] 8
##
## Iter: 1 fn: 138.4520 Pars: 0.0691362976 0.0000001194 0.9308635827 0.4358971394
## Iter: 2 fn: 138.4520 Pars: 0.06913626642 0.00000003935 0.93086369423 0.43589705238
## Iter: 3 fn: 138.4520 Pars: 0.0691363056726 0.0000000001597 0.9308636941681 0.4358972032714
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 139.4971 Pars: 0.04629 0.01800 0.93571 0.22222
## Iter: 2 fn: 139.4971 Pars: 0.04629 0.01800 0.93571 0.22222
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 116.8411 Pars: 0.03600 0.02100 0.94300 0.33332
## Iter: 2 fn: 116.8411 Pars: 0.03600 0.02100 0.94300 0.33333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 77.7518 Pars: 0.04900 0.01400 0.93700 0.71429
## Iter: 2 fn: 77.7518 Pars: 0.04900 0.01400 0.93700 0.71428
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 128.4439 Pars: 0.04800 0.03200 0.92000 0.50000
## Iter: 2 fn: 128.4439 Pars: 0.04800 0.03200 0.92000 0.50000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 120.3604 Pars: 0.04050 0.01125 0.94825 0.11111
## Iter: 2 fn: 120.3604 Pars: 0.04050 0.01125 0.94825 0.11111
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 106.8588 Pars: 0.01633 0.03267 0.95100 0.14279
## Iter: 2 fn: 106.8588 Pars: 0.01633 0.03267 0.95100 0.14286
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 159.1280 Pars: 0.04033 0.07333 0.88633 0.45455
## Iter: 2 fn: 159.1280 Pars: 0.04033 0.07333 0.88633 0.45455
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 189.4939 Pars: 0.06760 0.02860 0.90380 0.23078
## Iter: 2 fn: 189.4939 Pars: 0.06760 0.02860 0.90380 0.23077
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 174.6289 Pars: 0.06031 0.02369 0.91600 0.07143
## Iter: 2 fn: 174.6289 Pars: 0.06031 0.02369 0.91600 0.07143
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1389.8039 Pars: 0.04397 0.02323 0.93281 0.27672
## Iter: 2 fn: 1389.8038 Pars: 0.04397 0.02323 0.93281 0.27673
## solnp--> Completed in 2 iterations
## [1] 9
##
## Iter: 1 fn: 105.0705 Pars: 0.07199982872 0.00000006055 0.92800011044 0.66666604994
## Iter: 2 fn: 105.0705 Pars: 0.07199984310 0.00000001874 0.92800013815 0.66666605337
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 129.9523 Pars: 0.05290 0.00460 0.94250 0.13044
## Iter: 2 fn: 129.9523 Pars: 0.05290 0.00460 0.94250 0.13044
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 94.3171 Pars: 0.02450 0.02800 0.94750 0.42856
## Iter: 2 fn: 94.3171 Pars: 0.02450 0.02800 0.94750 0.42857
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 67.6779 Pars: 0.0845099419486 0.0000000006277 0.9154900571318 0.8461720339470
## Iter: 2 fn: 67.6779 Pars: 0.08449785454 0.00000000032 0.91550214514 0.84615043582
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 142.0349 Pars: 0.03756 0.03756 0.92489 0.30769
## Iter: 2 fn: 142.0349 Pars: 0.03756 0.03756 0.92489 0.30769
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 131.2505 Pars: 0.04813 0.01013 0.94173 0.21052
## Iter: 2 fn: 131.2505 Pars: 0.04813 0.01013 0.94173 0.21053
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 112.3169 Pars: 0.04000 0.02800 0.93200 0.49998
## Iter: 2 fn: 112.3169 Pars: 0.04000 0.02800 0.93200 0.50000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 186.6110 Pars: 0.06145 0.03073 0.90782 0.15385
## Iter: 2 fn: 186.6110 Pars: 0.06145 0.03073 0.90782 0.15385
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 180.2304 Pars: 0.0885963414 0.0000001728 0.9114034854 0.3114817103
## Iter: 2 fn: 180.2303 Pars: 0.08859327043 0.00000004167 0.91140668789 0.31146506929
## Iter: 3 fn: 180.2303 Pars: 0.088598103784 0.000000005886 0.911401890330 0.311490911864
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 182.4494 Pars: 0.0439999677 0.0459999574 0.9100000746 0.0000002526
## Iter: 2 fn: 182.4494 Pars: 0.0439999630 0.0459999571 0.9100000799 0.0000001461
## Iter: 3 fn: 182.4494 Pars: 0.04399995802 0.04599995709 0.91000008489 0.00000003035
## Iter: 4 fn: 182.4494 Pars: 0.043999956688 0.045999956823 0.910000086488 0.000000002915
## solnp--> Completed in 4 iterations
##
## Iter: 1 fn: 1386.4757 Pars: 0.04755 0.01835 0.93410 0.28070
## Iter: 2 fn: 1386.4757 Pars: 0.04755 0.01835 0.93410 0.28070
## solnp--> Completed in 2 iterations
## [1] 10
##
## Iter: 1 fn: 128.4439 Pars: 0.057142802903 0.000000007229 0.942857189576 0.299999831435
## Iter: 2 fn: 128.4439 Pars: 0.057142806076 0.000000001737 0.942857192187 0.299999844731
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 160.6000 Pars: 0.05188 0.02471 0.92341 0.19047
## Iter: 2 fn: 160.6000 Pars: 0.05188 0.02471 0.92341 0.19048
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 100.0937 Pars: 0.04050 0.02250 0.93700 0.55555
## Iter: 2 fn: 100.0937 Pars: 0.04050 0.02250 0.93700 0.55555
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 121.2452 Pars: 0.04800 0.02400 0.92800 0.49998
## Iter: 2 fn: 121.2452 Pars: 0.04800 0.02400 0.92800 0.50000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 118.5063 Pars: 0.06424384 0.00004192 0.93571425 0.53318186
## Iter: 2 fn: 118.5062 Pars: 0.0642847581 0.0000008747 0.9357143672 0.5333297539
## Iter: 3 fn: 118.5062 Pars: 0.0642849366 0.0000006959 0.9357143675 0.5333304101
## solnp--> Completed in 3 iterations
##
## Iter: 1 fn: 114.0325 Pars: 0.03462 0.01385 0.95154 0.13334
## Iter: 2 fn: 114.0325 Pars: 0.03462 0.01385 0.95154 0.13333
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 156.3493 Pars: 0.06453 0.01173 0.92373 0.31818
## Iter: 2 fn: 156.3493 Pars: 0.06453 0.01173 0.92373 0.31818
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 142.8815 Pars: 0.04444 0.02000 0.93556 0.10000
## Iter: 2 fn: 142.8815 Pars: 0.04444 0.02000 0.93556 0.10000
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 220.6438 Pars: 0.08736 0.03382 0.87882 0.29033
## Iter: 2 fn: 220.6438 Pars: 0.08736 0.03382 0.87882 0.29032
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 167.0704 Pars: 0.05009 0.02922 0.92069 0.04168
## Iter: 2 fn: 167.0704 Pars: 0.05009 0.02922 0.92070 0.04167
## solnp--> Completed in 2 iterations
##
## Iter: 1 fn: 1461.9631 Pars: 0.05249 0.01704 0.93047 0.27225
## Iter: 2 fn: 1461.9631 Pars: 0.05249 0.01704 0.93047 0.27225
## solnp--> Completed in 2 iterationssapply(lca_dk_stnd_err, function(x) round(head(x, 1),3))## $stnderrs.lca.params
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## lgg 0.01 0.009 0.009 0.043 0.009 0.01 0.017 0.01 0.021 0.006
##
## $avg.effects
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
## lca 0.005 0.02 0.02 0.025 0.019 0.012 0.026 0.029 0.03 0.033 0.02
##
## $stnderrs.effects
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
## lca 0.008 0.009 0.007 0.026 0.013 0.008 0.012 0.016 0.014 0.008 0.002fit <- fit_nodk(alldat[,t1], alldat[,t2], res$param.lca[4,], res$param.lca[1:3,])
print(fit[,1:4])## item1 item2 item3 item4
## chi-square 2.5791029 5.136378e+01 3.8689664 0.636025
## p-value 0.4611649 4.092471e-11 0.2759655 0.888138fit <- fit_dk(alldat_dk[,t1], alldat_dk[,t2], res_dk$param.lca[8,], res_dk$param.lca[1:7,], force9=TRUE)
print(fit[,1:4])## item1 item2 item3 item4
## chi-square Inf Inf Inf Inf
## p-value 0 0 0 0These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.