# File src/library/stats/R/logLik.R # Part of the R package, https://www.R-project.org # # Copyright (C) 2001-2014 The R Core Team # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # A copy of the GNU General Public License is available at # https://www.R-project.org/Licenses/ ### originally from package nlne. logLik <- function(object, ...) UseMethod("logLik") print.logLik <- function(x, digits = getOption("digits"), ...) { cat("'log Lik.' ", paste(format(c(x), digits = digits), collapse = ", "), " (df=", format(attr(x,"df")), ")\n", sep = "") invisible(x) } str.logLik <- function(object, digits = max(2L, getOption("digits") - 3L), vec.len = getOption("str")$vec.len, ...) { cl <- oldClass(object) len <- length(co <- c(object)) cutl <- len > vec.len cat("Class", if (length(cl) > 1L) "es", " '", paste(cl, collapse = "', '"), "' : ", paste (format(co[seq_len(min(len,vec.len))], digits = digits), collapse = ", "), if(cutl) ", ...", " (df=", format(attr(object,"df")), ")\n", sep = "") } ## rather silly (but potentially used in pkg nlme): as.data.frame.logLik <- function (x, ...) as.data.frame(c(x), ...) ## >> logLik.nls() in nls.R ## from package:nlme ## log-likelihood for glm objects logLik.glm <- function(object, ...) { if(!missing(...)) warning("extra arguments discarded") fam <- family(object)$family dispersion <- family(object)$dispersion p <- object$rank ## allow for estimated dispersion if (!is.null(dispersion)) { if (is.na(dispersion)) p <- p + 1 } else if(fam %in% c("gaussian", "Gamma", "inverse.gaussian")) p <- p + 1 val <- p - object$aic / 2 ## Note: zero prior weights have NA working residuals. attr(val, "nobs") <- sum(!is.na(object$residuals)) attr(val, "df") <- p class(val) <- "logLik" val } ## log-likelihood for lm objects logLik.lm <- function(object, REML = FALSE, ...) { if(inherits(object, "mlm")) stop("'logLik.lm' does not support multiple responses") res <- object$residuals # not resid(object) because of NA methods p <- object$rank N <- length(res) if(is.null(w <- object$weights)) { w <- rep.int(1, N) } else { ## this is OK as both resids and weights are for the cases used excl <- w == 0 # eliminating zero weights if (any(excl)) { res <- res[!excl] N <- length(res) w <- w[!excl] } } N0 <- N if(REML) N <- N - p val <- .5* (sum(log(w)) - N * (log(2 * pi) + 1 - log(N) + log(sum(w*res^2)))) if(REML) val <- val - sum(log(abs(diag(object$qr$qr)[1L:p]))) attr(val, "nall") <- N0 # NB, still omits zero weights attr(val, "nobs") <- N attr(val, "df") <- p + 1 class(val) <- "logLik" val } ## Since AIC, BIC call logLik on everything logLik.logLik <- function(object, ...) object nobs <- function(object, ...) UseMethod("nobs") ## also used for mlm fits nobs.lm <- function(object, ...) if(!is.null(w <- object$weights)) sum(w != 0) else NROW(object$residuals) nobs.glm <- function(object, ...) if(!is.null(w <- object$prior.weights)) sum(w != 0) else length(object$residuals) nobs.logLik <- function(object, ...) { res <- attr(object, "nobs") if (is.null(res)) stop("no \"nobs\" attribute is available") res } nobs.nls <- function(object, ...) if (is.null(w <- object$weights)) length(object$m$resid()) else sum(w != 0) ## it is probably too unsafe to use residuals generally, not least ## because of e.g. weighted fits. nobs.default <- function(object, use.fallback = FALSE, ...) { ## MASS::loglm and MASS::polr fits have an 'nobs' component if((is.L <- is.list(object)) && !is.null(n <- object[["nobs"]])) n ## cov.wt() unfortunately uses 'n.obs': else if(is.L && !is.null(n <- object[["n.obs"]])) n else if(use.fallback) { if(!is.null(w <- object[["weights"]])) sum(w != 0) else if("residuals" %in% names(object)) NROW(object$residuals) # and not residuals(object) ## perhaps sum(!is.na(object$residuals)) ? else { warning("no 'nobs' method is available") 0L # which is what object$residuals used to give. } } else stop("no 'nobs' method is available") # or maybe NA_integer_ }