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# All arguments as in `graphics::text`, except pad which specifies padding (optionally 
# for vertical and horizontal) around the text as a fraction of a character width.
# `...` is passed to `rect`
textbox <-
function(x, y, labels, adj = NULL,
         pos = NULL,
         offset = 0.5,
         pad = c(0, 0),
         vfont = NULL,
         cex = par("cex"),

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@echo off
setlocal EnableDelayedExpansion

set result=
set outfile=
set nextisoutfile=

set "self=%~n0"

:startHelp

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require("MuMIn")

local({

quasiLik.compar.gee <-
function (object, ...) {
    scale <- object$scale
    ret <- .qlik(object$residuals + object$fitted.values, object$fitted.values,
        get(object$family, envir = asNamespace("stats"))(), 
        1, scale)

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local({

family.phylolm <-
function (object, ...) {
    stop("???")
}

logLik.pglmm_compare <-
function (object, ...) {
    rval <- object$logLik

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sd.ranef.avg <-
function(object) {
    
    if(!inherits(object, "averaging"))
        stop("not an \"averaging\" object")

    mo <- get.models(object, TRUE)
    re <-  lapply(mo, function(x) as.data.frame(ranef(x, condVar = TRUE)))
    
    cols <- c("grpvar", "term", "grp")

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#' @return a two-column matrix of turning angles `"ta"` and step lengths `"len"`.
#' @param Nstates the number of movement states. 
#' @param tp a vector of transition probabilities for `Nstates == 2` or a
#' square transition matrix `[Nstates, Nstates]`. Ignored if `Nstates == 1` 
#' @param mu,rho wrapped Cauchy distribution parameters for the turning angles. Should have a length of `Nstates`.
#' @param wscale,wshape Weibull distribution parameters for step length
# TODO: starting position and initial direction. Currently all are set to 0.
mscrwpath <-
function(N, Nstates = 2, tp = c(.05, .1),
		 mu = c(0, 0), rho = c(.5, .99),

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#' @param formula,data,subset,na.action arguments to `model.frame`. If the first argument is a data frame, the rest is ignored. 
#' @param method argument to `cor.test`. A character string indicating which correlation coefficient is to be used for the test. One of "pearson", "kendall", or "spearman", can be abbreviated.
#' @param n integer; the number of x values at which to evaluate.
#' @param lty,col,cex graphical parameters fit line type, line colour, character expansion for labels.
#' @param \dots optional, additional arguments passed to `points`
#' @example
#' data <- data.frame(x = runif(100), x1 = rlnorm(100), x2 = rnorm(100))
#' pairs.cor(~ x + log(x1) + x2, data)
pairs.cor <-
function(formula, data = NULL, subset = NULL, na.action = na.fail,

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# The syntax is very much as in `boxplot` (a large portion of the code is taken 
# from graphics::boxplot.default and graphics::bxp).
# The argument `density.args` should be a named list and is used to pass arguments to `density`.

violplot <-
function (x, ...) 
UseMethod("violplot")

registerS3method("violplot", "formula", 
function (formula, data = NULL, ..., subset, na.action = NULL, 

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#' @param \dots two or more `logLik` objects
lrt <-
function(...) {
    logL <- list(...)
    nmodels <- length(logL)
    rval <- matrix(rep(NA, 5 * nmodels), ncol = 5)
    colnames(rval) <- c("#Df", "LogLik", "Df", "Chisq", "Pr(>Chisq)")
    rownames(rval) <- 1:nmodels
    rval[, 1] <- as.numeric(sapply(logL, function(x) attr(x, "df")))

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weighted.histogram <-
function() {
    cl <- match.call()
    cl$w <- NULL
    cl[[1L]] <- as.name("hist.default")
    cl$plot <- FALSE
    h <- eval.parent(cl)
    f <- factor(findInterval(x, h$breaks, left.open = TRUE,
        rightmost.closed = TRUE,
        all.inside = TRUE),