R/summary.LassoGEE.R

In LassoGEE: High-Dimensional Lasso Generalized Estimating Equations

summary.LassoGEE <- function(object, correlation = TRUE, ...) {
    coef <- object$betaest
    resid <- object$residuals
    n <- length(resid)
    # p <- object$rank
    # if(is.null(p))
    #     p <- sum(!is.na(coef))
    # if(!p) {
    #     warning("This model has zero rank --- no summary is provided")
    #     return(object)
    # }
    nas <- is.na(coef)
    cnames <- names(coef[!nas])
    # coef <- matrix(rep(coef[!nas], 5), ncol = 5)
    # dimnames(coef) <- list(cnames, c("Estimate",
    #                                  "Naive S.E.",  "Naive z",
    #                                  "Robust S.E.", "Robust z"))
    # rse <- sqrt(diag(object$robust.variance))
    # nse <- sqrt(diag(object$naive.variance))
    # coef[,2] <- nse
    # coef[,3] <- coef[,1]/coef[,2]
    # coef[,4] <- rse
    # coef[,5] <- coef[,1]/coef[,4]
    summary <- list()
    summary$call <- object$call
    summary$version <- object$version
    summary$nobs <- object$nobs
    summary$residual.summary <- quantile(as.vector(object$residuals))
    names(summary$residual.summary) <- c("Min", "1Q", "Median", "3Q", "Max")
    summary$model<- object$model
    summary$title <- object$title
    summary$betaest <- coef
    summary$scale <- object$scale
    summary$lambda.value <-object$lambda.value
    summary$error <- paste("Error code was", object$error)
    summary$working.correlation <- object$working.correlation
    summary$outer.iter <- object$outer.iter
    if ( correlation ) {
        ##	rob.var <- object$robust.variance
        ##	nai.var <- object$naive.variance
        ##	summary$robust.correlation <- rob.var /
        ##	outer(sqrt(diag(rob.var)),sqrt(diag(rob.var)))
        ##	dimnames(summary$robust.correlation) <- list(object$xnames,object$xnames)
        ##	summary$naive.correlation <- nai.var /
        ##	outer(sqrt(diag(nai.var)),sqrt(diag(nai.var)))
        ##	dimnames(summary$naive.correlation) <- list(object$xnames,object$xnames)
    }
    attr(summary,"class") <- "summary.LassoGEE"
    summary
}