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A package for R to estimate private-value auction models while allowing for unobservable auction-specific heterogeneity.
# Install auctionr from CRAN
install.packages("auctionr")
# Or the development version from GitHub:
# install.packages("remotes")
# library(remotes)
install_github("ajmack/auctionr", build_vignettes = T)There are two functions available in the package:
auction_generate_data() allows the user to generate
sample data from the principal model used in the package.
auction_model() calculates maximum likelihood
estimates of parameters of the principal model for the data provided by
the user.
library(auctionr)
set.seed(100)
dat <- auction_generate_data(obs = 100, mu = 10, alpha = 2, sigma = 0.2,
beta = c(-1,1), new_x_mean= c(-1,1), new_x_sd = c(0.5,0.8))
res <- auction_model(dat,
init_param = c(8, 2, .5, .4, .6),
num_cores = 1,
method = "BFGS",
control = list(trace=1, parscale = c(1,0.1,0.1,1,1)),
std_err = TRUE)## initial value 1339.327262
## iter 10 value 434.301377
## iter 20 value 410.711195
## final value 410.710822
## converged
## res##
## Estimated parameters (SE):
## mu 11.012673 (1.152635)
## alpha 1.752769 (0.185499)
## sigma 0.204230 (0.035286)
## beta[1] -0.920617 (0.057040)
## beta[2] 1.068096 (0.040026)
##
## Maximum log-likelihood = -410.711Background and details about the model implemented here are available in Mackay, Alexander. 2020. Contract Duration and the Costs of Market Transactions..
These 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.