R/elnormAltCensored.R

In EnvStats: Package for Environmental Statistics, Including US EPA Guidance

elnormAltCensored <-
function (x, censored, method = "mle", censoring.side = "left", 
    ci = FALSE, ci.method = "profile.likelihood", ci.type = "two-sided", 
    conf.level = 0.95, n.bootstraps = 1000, pivot.statistic = "z", 
    ...) 
{
    if (!is.vector(x, mode = "numeric")) 
        stop("'x' must be a numeric vector")
    if (!is.vector(censored, mode = "numeric") && !is.vector(censored, 
        mode = "logical")) 
        stop("'censored' must be a logical or numeric vector")
    if (length(censored) != length(x)) 
        stop("'censored' must be the same length as 'x'")
    data.name <- deparse(substitute(x))
    censoring.name <- deparse(substitute(censored))
    if ((bad.obs <- sum(!(ok <- is.finite(x) & is.finite(as.numeric(censored))))) > 
        0) {
        x <- x[ok]
        censored <- censored[ok]
        warning(paste(bad.obs, "observations with NA/NaN/Inf in 'x' and 'censored' removed."))
    }
    if (is.numeric(censored)) {
        if (!all(censored == 0 | censored == 1)) 
            stop(paste("When 'censored' is a numeric vector, all values of", 
                "'censored' must be 0 (not censored) or 1 (censored)."))
        censored <- as.logical(censored)
    }
    n.cen <- sum(censored)
    if (n.cen == 0) 
        stop("No censored values indicated by 'censored'.")
    if (any(x <= 0)) 
        stop("All values of 'x' (including censored ones) must be positive")
    x.no.cen <- x[!censored]
    if (length(unique(x.no.cen)) < 2) 
        stop("'x' must contain at least 2 non-missing, uncensored, distinct values.")
    censoring.side <- match.arg(censoring.side, c("left", "right"))
    ci.type <- match.arg(ci.type, c("two-sided", "lower", "upper"))
    pivot.statistic <- match.arg(pivot.statistic, c("z", "t"))
    multiple <- TRUE
    T.vec <- unique(x[censored])
    if (length(T.vec) == 1) {
        if (censoring.side == "left") {
            if (T.vec <= min(x.no.cen)) 
                multiple <- FALSE
        }
        else {
            if (T.vec >= max(x.no.cen)) 
                multiple <- FALSE
        }
    }
    adj <- FALSE
    if(ci && ci.method == "profile.likelihood") {
        if(censoring.side == "left") {
            mf <- 10^ceiling(log((1/max(x)), 10))
            if(mf > 1) {
                adj <- TRUE
                x <- mf * x
            }
        }
    }
    args.list <- list(x = x, censored = censored, method = method, 
        censoring.side = censoring.side, ci = ci, ci.method = ci.method, 
        ci.type = ci.type, conf.level = conf.level, n.bootstraps = n.bootstraps, 
        pivot.statistic = pivot.statistic, ...)
    if (multiple) {
        ret.list <- do.call("elnormAltMultiplyCensored", args = args.list)
    }
    else {
        ret.list <- do.call("elnormAltSinglyCensored", args = args.list)
    }
    if(adj) {
        ret.list$parameters <- ret.list$parameters/mf
        ret.list$interval$limits <- ret.list$interval$limits/mf
    }
    ret.list$data.name <- data.name
    ret.list$censoring.name <- censoring.name
    ret.list
}