Nothing
poisson.fit <-
function (x, y, weights, tol = 1e-08, max.iter = 25, verbose = FALSE)
{
if (!is.matrix(x))
x <- as.matrix(x)
nvars <- NCOL(x)
nobs <- NROW(x)
mu <- y + 0.1 ##
eta <- log(mu) ##
iter <- 0
prev.dev <- dev.increase <- Inf
while (dev.increase >= tol & iter <= max.iter) {
iter <- iter + 1
z <- eta + (y - mu)/mu ##
ww <- sqrt(weights * mu)
fit <- .Fortran("dqrls", qr = x * ww, n = nobs, p = nvars,
y = ww * z, ny = as.integer(1), tol = min(1e-07,
glm.control()$epsilon/1000), coefficients = double(nvars),
residuals = double(nobs), effects = double(nobs),
rank = integer(1), pivot = 1:nvars, qraux = double(nvars),
work = double(2 * nvars), PACKAGE = "CNVassoc")
coeffic <- fit$coefficients
eta <- drop(x %*% coeffic)
mu <- exp(eta)
cur.dev <- -2 * sum(y * eta - mu) ##
dev.increase <- abs(prev.dev - cur.dev)
prev.dev <- cur.dev
if (verbose)
cat("Deviance iter", iter, "=", cur.dev, "\n")
}
coeffic <- as.vector(coeffic)
names(coeffic) <- colnames(x)
return(coeffic)
}
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