linmodEst <- function(x, y) {
## compute QR-decomposition of x
qx <- qr(x)
## compute (x’x)^(-1) x’y
coef <- solve.qr(qx, y)
## degrees of freedom and standard deviation of residuals
df <- nrow(x) - ncol(x)
sigma2 <- sum((y - x %*% coef) ^ 2) / df
## compute sigma^2 * (x’x)^-1
vcov <- sigma2 * chol2inv(qx$qr)
colnames(vcov) <- rownames(vcov) <- colnames(x)
list(
coefficients = coef,
vcov = vcov,
sigma = sqrt(sigma2),
df = df
)
}
linmod <- function(x, ...)
UseMethod("linmod")
linmod.default <- function(x, y, ...) {
x <- as.matrix(x)
y <- as.numeric(y)
est <- linmodEst(x, y)
est$fitted.values <- as.vector(x %*% est$coefficients)
est$residuals <- y - est$fitted.values
est$call <- match.call()
class(est) <- "linmod"
return(est)
}
linmod.formula <- function(formula, data = list(), ...) {
mf <- model.frame(formula = formula, data = data)
x <- model.matrix(attr(mf, "terms"), data = mf)
y <- model.response(mf)
est <- linmod.default(x, y, ...)
est$call <- match.call()
est$formula <- formula
return(est)
}
print.linmod <- function(x, ...) {
cat("Call:\n")
print(x$call)
cat("\nCoefficients:\n")
print(x$coefficients)
}
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