Nothing
library(stratEst)
test_that("Example: rock-paper-scissors" , {
skip_on_cran()
set.seed(1)
strategies.mixture = list( "nash" = strategies.RPS$nash, "imitate" = strategies.RPS$imitate )
model.mixture <- stratEst.model(data.WXZ2014,strategies.mixture)
expect_equal(-22358.43,round(model.mixture$loglike,2))
})
test_that("Example: Dal Bo & Frechette 2011", {
skip_on_cran()
set.seed(1)
data <- stratEst.data(DF2011,input =c("choice","other.choice"), input.lag = 1 )
model.DF2011 <- stratEst.model(data,strategies.DF2011,sample.id="treatment",verbose=F)
expect_equal(0.920,round(as.numeric(model.DF2011$shares$treatment.D5R32[1]),3))
expect_equal(0.080,round(as.numeric(model.DF2011$shares$treatment.D5R32[4]),3))
expect_equal(0.043,round(as.numeric(model.DF2011$shares.se[1]),3))
expect_equal(0.043,round(as.numeric(model.DF2011$shares.se[4]),3))
expect_equal(0.362,round(as.numeric(model.DF2011$gammas.par[1]),3))
})
# test_that("Example: Fudenberg, Rand, Dreber (2012)" , {
# skip_on_cran()
# set.seed(1)
# data <- stratEst.data(FRD2012,input =c("last.choice","last.other") )
# model.FRD2012 <- stratEst.model(data,strategies.FRD2012,sample.id="bc",verbose=F)
# expect_equal(0.193,round(as.numeric(model.FRD2012$shares$bc.1.5[2]),3))
# expect_equal(0.139,round(as.numeric(model.FRD2012$shares$bc.1.5[7]),3))
# expect_equal(0.053,round(as.numeric(model.FRD2012$shares.se[2]),3))
# expect_equal(0.035,round(as.numeric(model.FRD2012$shares.se[3]),3))
# expect_equal(0.46,round(as.numeric(model.FRD2012$gammas.par[1]),2))
# })
test_that("Example: Dvorak, Fischbacher, and Schmelz (2020)" , {
skip_on_cran()
data.DFS2020 <- stratEst.data(data = DFS2020,
input = c("others.choices"))
model.DFS2020 <- stratEst.model(data = data.DFS2020 ,
strategies = strategies.DFS2020,
covariates = c("intercept","conformity.score"))
test.coefficients <- stratEst.test(model.DFS2020, par = "coefficients")
expect_equal(0.008,round(as.numeric(test.coefficients$p.value[1]),3))
expect_equal(0.007,round(as.numeric(test.coefficients$p.value[2]),3))
check.DFS2020 <- stratEst.check(model.DFS2020, chi.tests = TRUE, bs.samples = 1)
expect_equal(0.0855,round(as.numeric(check.DFS2020$chi.global[1,1]),4))
expect_equal(52.2931,round(as.numeric(check.DFS2020$chi.local[1,1]),4))
expect_equal(117.7065,round(as.numeric(check.DFS2020$chi.local[2,1]),4))
})
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