Jor*_*eys 13
不,你不能直接使用强大的vcov函数confint.但手动执行此操作非常简单.
x <- sin(1:100)
y <- 1 + x + rnorm(100)
## model fit and HC3 covariance
fm <- lm(y ~ x)
Cov <- vcovHC(fm)
tt <-qt(c(0.025,0.975),summary(fm)$df[2])
se <- sqrt(diag(Cov))
ci <-coef(fm) + se %o% tt
否则,您可以根据confint.default()自己的需要调整功能:
confint.robust <- function (object, parm, level = 0.95, ...)
{
    cf <- coef(object)
    pnames <- names(cf)
    if (missing(parm))
        parm <- pnames
    else if (is.numeric(parm))
        parm <- pnames[parm]
    a <- (1 - level)/2
    a <- c(a, 1 - a)
    pct <- stats:::format.perc(a, 3)
    fac <- qnorm(a)
    ci <- array(NA, dim = c(length(parm), 2L), dimnames = list(parm,
        pct))
    ses <- sqrt(diag(sandwich::vcovHC(object)))[parm]
    ci[] <- cf[parm] + ses %o% fac
    ci
}
正如Brandon已经建议的那样,如果你在stats.stackexchange.com上提出这些问题,你会有更多的机会快速回答