##' \code{loadings(object)} and then design your own plotting method. ##' @title Side by side scores and loadings plot ##' @usage slplot(object, pcs=c(1,2), scoresLoadings=c(TRUE, TRUE), ##' sl="def", ll="def", hotelling=0.95, rug=TRUE, sub=NULL,...) ##' @param object ##' @param pcs ##' @param tjo ##' @return None, used for side effect. ##' @export ##' @author Henning Redestig setMethod("slplot", "pcaRes", function(object, pcs=c(1,2), tjo) { #(ess-roxy-get-function-args) opar <- par(no.readonly=TRUE) cl <- match.call() }) ##' .. content for \description{} (no empty lines) .. ##' ##' .. content for \details{} .. ##' @title ##' @param a ##' @param b ##' @param d ##' @param asd ##' @return ##' @author Henning Redestig trickyInArgsComments <- function(a,#comment b,#hejhopp trams d,asd) { print("hello") } ##' .. content for \description{} (no empty lines) .. ##' ##' .. content for \details{} .. ##' @title ##' @param a ##' @param b ##' @param cc ##' @return ##' @author Henning Redestig withdef <- function(a, b=c("asd","ffd", "asd", "ffd", "asd", "ffd","asd", "ffd"), cc) { print("hello") } setClass(Class="inference", representation=representation(model="character" , sample.size="numeric" , robust.se="logical" , two.sided="logical" , ci.level="numeric"), contains=c("matrix")) ##' .. content for \description{} (no empty lines) ##' ##' .. content for \details{} .. ##' @title asd ##' @param a ##' @param asdsd ##' @param sd ##' @param ... ##' @return s ##' @author Henning Redestig tempFixNasFunction <- function(a,asdsd, sd, ...) { asds } setGeneric("updateMu", function(respM, gamma, ...) standardGeneric("updateMu")) ## (make-local-variable 'adaptive-fill-regexp) ## (setq adaptive-fill-regexp (concat ess-roxy-str adaptive-fill-regexp)) ## (make-local-variable 'adaptive-fill-first-line-regexp) ## (setq adaptive-fill-first-line-regexp (concat ess-roxy-str adaptive-fill-first-line-regexp)) ## (make-local-variable 'paragraph-start) ## (setq paragraph-start (concat "\\(" ess-roxy-str "\\)*" paragraph-start)) ## (make-local-variable 'paragraph-separate) ## (setq paragraph-separate (concat "\\(" ess-roxy-str "\\)*" paragraph-separate)) ## (auto-fill-mode) asd ##' aqdasd lksa odnsl dlsakdn lsakdn sladn asijdi j 1. asdsd alksnd ##' lasdn ldnad ##' ##' ##' alkdnal dl lakd lasdnladna ld aldan lda dlakd nladn a amd lakdn ##' ajdn asjdns ##' ##' lajnsd jasdn aksjdnaksjnd asjdnaksdnajsdnajsd aksdn askdjn ##' akjdn aksdnkasjdnka ##' ##' 1. aldn adlnsald ladn saldnlaksd naskl ##' 2. ad asdjnksadn adjn skajan kda dksadkas dkjan dkasndkadn ##' ajsd nkj dakjd sd ##' @title hej ##' @param fitta asdadsd ##' 1. ##' 2. asd ##' @param diagonals pung asa as a sad s dsa da das d asd asd ##' add ##' @param tjo asd ##' @param asdasd ##' @return me ##' @author Henning Redestig tempFixNas <- function(fitta, diagonals, tjo, asdasd) { for(i in index) { data <- otherdata[i] } } ##' Simply replace completely ajksbdkjsa djskbdkajbd ##' ##' ksdb skdb skasdaj ahd (ess-roxy-beg-of-field) (newline-and-indent) ##' aksndlsakndlksdn jkahd ksn dkjands ##' @title Temporary fix for missing values ##' @param diagonals The diagonal to be replaced, i.e. the first, ##' second and so on when looking at the fat version of the matrix ##' @param tjo asdsdsdw ##' @return The original matrix with completely missing rows/cols ##' filled with zeroes. oasndsnd aksdnkasdnskans dkas ndkjasndksdn ##' skandkand ksjandknsd ##' @export ##' @examples ##' tempFixNas(iris) ##' pi <- 1 ##' plot(x) ##' @author Henning Redestig tempFixNas <- function(diagonals, tjo) { (ess-roxy-delete-args) wilcox.test (ess-roxy-goto-end-of-entry) badRows <- apply(mat, 1, function(x) all(is.na(x))) badCols <- apply(mat, 2, function(x) all(is.na(x))) mat[ badRows,] <- 0 (ess-roxy-get-args-list-from-def) mat[,badCols ] <- 0 (ess-roxy-get-args-list-from-entry) mat } ##' ##' ##'
##' @title asdsd ##' @param asd asd ##' @param test1 asd ##' @param asdsd ##' @param tjo asdasd ##' @return aa ##' @author Henning Redestig tempFixNas <- function(asd,test1,asdsd,tjo=c("asd", "asdasd")) { ## (ess-roxy-goto-end-of-entry) ## (setq fun (ess-roxy-get-args-list-from-def)) ## (setq ent (ess-roxy-get-args-list-from-entry)) ## (ess-roxy-merge-args fun ent) ## (ess-roxy-mrg-args fun ent) ## (ess-roxy-get-args-list-from-entry) ## (ess-roxy-get-function-args) ## (ess-roxy-goto-end-of-entry) ## (setq here (ess-roxy-delete-args)) ## (ess-roxy-insert-args (ess-roxy-get-args-list-from-def) here) badRows <- apply(mat, 1, function(x) all(is.na(x))) badCols <- apply(mat, 2, function(x) all(is.na(x))) mat[ badRows,] <- 0 mat[,badCols ] <- 0 mat } ##' ##' ##'
##' @title my title ##' @param test1 ##' @param tjo ##' @param pung ##' @param str ##' @return value ##' @author Henning Redestig tempFixNasBad <- function(test1,tjo=c("asd", "asdasd"), pung, str) { asdsd# (car (cdr (ess-end-of-function nil t))) } ##' Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse ##' Non-Linear PCA and the conventional SVD PCA. A cluster based ##' method for missing value estimation is included for comparison. ##' BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete ##' data as well as for accurate missing value estimation. A set of ##' methods for printing and plotting the results is also provided. ##' All PCA methods make use of the same data structure (pcaRes) to ##' provide a unique interface to the PCA results. Developed at the ##' Max-Planck Institute for Molecular Plant Physiology, Golm, ##' Germany, RIKEN Plant Science Center Yokohama, Japan, and CAS-MPG ##' Partner Institute for Computational Biology (PICB) Shanghai, ##' P.R. China ##' ##' @name pcaMethods ##' @aliases pcaMethods ##' @docType package ##' @title pcaMethods ##' @useDynLib pcaMethods ##' @author Wolfram Stacklies, Henning Redestig NULL asdsd