Last updated on 2025-03-11 14:55:58 CET.
Package | ERROR | OK |
---|---|---|
DiceKriging | 15 | |
kergp | 2 | 13 |
Current CRAN status: OK: 15
Current CRAN status: ERROR: 2, OK: 13
Version: 0.5.8
Check: examples
Result: ERROR
Running examples in ‘kergp-Ex.R’ failed
The error most likely occurred in:
> ### Name: gp
> ### Title: Gaussian Process Model
> ### Aliases: gp
>
> ### ** Examples
>
> ## ==================================================================
> ## Example 1. Data sampled from a GP model with a known covTS object
> ## ==================================================================
> set.seed(1234)
> myCov <- covTS(inputs = c("Temp", "Humid"),
+ kernel = "k1Matern5_2",
+ dep = c(range = "input"),
+ value = c(range = 0.4))
> ## change coefficients (variances)
> coef(myCov) <- c(0.5, 0.8, 2, 16)
> d <- myCov@d; n <- 20
> ## design matrix
> X <- matrix(runif(n*d), nrow = n, ncol = d)
> colnames(X) <- inputNames(myCov)
> ## generate the GP realization
> myGp <- gp(formula = y ~ 1, data = data.frame(y = rep(0, n), X),
+ cov = myCov, estim = FALSE,
+ beta = 10, varNoise = 0.05)
> y <- simulate(myGp, cond = FALSE)$sim
Loading required package: MASS
>
> ## parIni: add noise to true parameters
> parCovIni <- coef(myCov)
> parCovIni[] <- 0.9 * parCovIni[] + 0.1 * runif(length(parCovIni))
> coefLower(myCov) <- rep(1e-2, 4)
> coefUpper(myCov) <- c(5, 5, 20, 20)
> est <- gp(y ~ 1, data = data.frame(y = y, X),
+ cov = myCov,
+ noise = TRUE,
+ varNoiseLower = 1e-2,
+ varNoiseIni = 1.0,
+ parCovIni = parCovIni)
Warning in nloptr.add.default.options(opts.user = opts, x0 = x0, num_constraints_ineq = num_constraints_ineq, :
No termination criterion specified, using default(relative x-tolerance = 1e-04)
Error in fitList[[bestIndex]] :
attempt to select less than one element in get1index
Error in gp(y ~ 1, data = data.frame(y = y, X), cov = myCov, noise = TRUE, :
Maximum Likelihood error
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
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