rfitv2:

In musto101/wilcox_R: What the package does (short line)

Usage

rfitv2(formula, data, subset, yhat0 = NULL, scores = Rfit::wscores, symmetric = FALSE, TAU = "F0", ...)

Arguments

formula
data
subset
yhat0
scores
symmetric
TAU
...

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (formula, data, subset, yhat0 = NULL, scores = Rfit::wscores, 
    symmetric = FALSE, TAU = "F0", ...) 
{
    call <- match.call()
    mf <- match.call(expand.dots = FALSE)
    m <- match(c("formula", "data", "subset"), names(mf), 0)
    mf <- mf[c(1, m)]
    mf[[1]] <- as.name("model.frame")
    mf <- eval.parent(mf)
    x <- model.matrix(attr(mf, "terms"), data = mf)
    if (abs(max(x) - min(x)) < .Machine$double.eps^0.5) 
        stop("x cannot only contain an intercept")
    x1 <- as.matrix(x[, colnames(x) != "(Intercept)"])
    x1 <- as.matrix(cbind(rep(1, nrow(x1)), x1))
    y <- model.response(mf)
    qrx <- qr(x1)
    Q <- as.matrix(qr.Q(qrx))
    q1 <- Q[, 1]
    xq <- as.matrix(Q[, 2:qrx$rank])
    if (is.null(yhat0)) {
        fit0 <- suppressWarnings(rq(y ~ xq - 1))
    }
    else {
        fit0 <- lsfit(xq, yhat0, intercept = FALSE)
    }
    betahat0 <- fit0$coef
    if (disp(betahat0, xq, y, scores) > disp(rep(0, length(betahat0)), 
        xq, y, scores)) {
        betahat0 <- rep(0, length(betahat0))
    }
    ord <- order(y - xq %*% betahat0)
    fit <- jaeckel(as.matrix(xq[ord, ]), y[ord], betahat0, scores = scores, 
        ...)
    if (fit$convergence != 0) {
        fit2 <- jaeckel(as.matrix(xq[ord, ]), y[ord], jitter(fit$par), 
            scores = scores, ...)
        if (fit$convergence != 0) {
            warning("rfit: Convergence status not zero in jaeckel")
            if (fit2$value < fit$value) 
                fit <- fit2
        }
        else {
            fit <- fit2
        }
        rm(fit2)
    }
    rm(ord)
    betahat <- fit$par
    yhat <- xq %*% betahat
    ehat <- y - yhat
    alphahat <- ifelse(symmetric, signedrank(ehat), median(ehat))
    ehat <- ehat - alphahat
    yhat <- yhat + alphahat
    bhat <- lsfit(x, yhat, intercept = FALSE)$coef
    r.gettau <- switch(TAU, F0 = gettauF0, R = gettau, N = function(...) NA)
    tauhat <- r.gettau(ehat, ncol(xq), scores, ...)
    if (symmetric) {
        taushat <- tauhat
    }
    else {
        taushat <- taustar(ehat, qrx$rank)
    }
    res <- list(coefficients = bhat, residuals = ehat, fitted.values = yhat, 
        scores = scores, x = x, y = y, tauhat = tauhat, qrx1 = qrx, 
        taushat = taushat, symmetric = symmetric, betahat = bhat, 
        disp = fit$value)
    res$call <- call
    class(res) <- list("rfit")
    res
  }

musto101/wilcox_R documentation built on May 23, 2019, 10:52 a.m.