Nothing
context("robust ee")
test_that("estimation equations are computed correctly", {
set.seed(1)
X <- cbind(1, 1:10)
u <- rnorm(10)
sigu <- var(u)
y <- X %*% c(1, 1) + u
matV <- matVFH(sigu, rep(0.01, 10))
coefs <- .lm.fit(X, y)$coefficients
uest <- .lm.fit(X, y)$residuals
ree <- robEstEqu(y, X, coefs, uest, matV, identity, 1)
testthat::expect_equal(ree$beta(), c(0, 0))
# How to get the other vals to zero without fitting the model is beyond me:
testthat::expect_is(ree$delta(), "numeric")
testthat::expect_equal(length(ree$delta()), 1)
testthat::expect_is(ree$re(), "numeric")
testthat::expect_equal(length(ree$re()), 10)
})
test_that("score interface", {
library("saeSim")
set.seed(1)
dat <- base_id(10, 1) %>%
sim_gen_e() %>%
sim_gen_x() %>%
sim_gen_v(sd = 2) %>%
sim_resp_eq(y = 100 + 2 * x + v + e) %>%
as.data.frame
y <- dat$y
X <- cbind(1, dat$x)
samplingVar <- rep(1, nrow(dat))
out <- saeRobust:::fitrfh(y, X, samplingVar)
scores <- score(out)
testthat::expect_equal(unlist(scores), rep(0, 13), tolerance = 10, check.attributes = FALSE)
})
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