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library("mbrglm")
data("lizards", package = "brglm2")
data("endometrial",package = "brglm2")
links <- lapply(c("logit", "probit", "cloglog", "cauchit"), make.link)
tol <- 1e-10
mbrglmControl <- mbrglm.control(mbr.epsilon = 1e-10, mbr.maxit = 1000)
for (l in seq_along(links)) {
## Lizards
lizardsFormula <- cbind(grahami, opalinus) ~ height + diameter + light + time
lizardsMBRlegacy <- mbrglm(lizardsFormula, family = binomial(links[[l]]), data = lizards,
method = "mbrglm.fit",
control.mbrglm = mbrglmControl)
expect_warning(lizardsMBR <- glm(lizardsFormula, family = binomial(links[[l]]), data = lizards,
method = "brglmFit", type="AS_median", epsilon = 1e-10, maxit = 1000))
## Endometrial
endoFormula <- HG ~ NV + PI + EH
expect_warning({
endoMBRlegacy <- mbrglm(endoFormula, family = binomial(links[[l]]), data = endometrial,
method = "mbrglm.fit",
control.mbrglm = mbrglmControl)
endoMBR <- glm(endoFormula, family = binomial(links[[l]]), data = endometrial,
method = "brglmFit", type = "AS_median", epsilon = 1e-10, maxit = 1000)
})
c1 <- coef(summary(endoMBRlegacy))
c2 <- coef(summary(endoMBR))
## glm with brglmFit method and mbrglm return the same coefficients when link is" links[[l]]$name
expect_equal(coef(lizardsMBR), coef(lizardsMBRlegacy), tolerance = tol)
expect_equal(c1, c2, tolerance = tol)
}
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