From a3189281ab15464e43d8a5c210e000b1b32125ae Mon Sep 17 00:00:00 2001 From: dcaff Date: Thu, 25 Apr 2013 11:52:15 -0600 Subject: [PATCH 1/2] updated description --- R/jackknife.R | 37 +++++++++++++++++++++++++++++++++++++ 1 file changed, 37 insertions(+) create mode 100644 R/jackknife.R diff --git a/R/jackknife.R b/R/jackknife.R new file mode 100644 index 0000000..9c2a209 --- /dev/null +++ b/R/jackknife.R @@ -0,0 +1,37 @@ +#' Resamples Data using the Jackknife Method +#' +#' @description +#' This function is used for estimating standard errors when the distribution is not know. +#' +#' @param x a vector +#' @param t estimation of parameter +#' +#' @return est orignial estimation of parameter +#' @return jkest jackknife estimation of parameter +#' @return jkvar jackknife estimation of variance +#' @return jkbias jackknife estimate of biasness of parameter +#' @return jkbiascorr bias corrected parameter estimate +#' +#' @author Damon McCafferty \email{damon.mccafferty@@economics.utah.edu} +#' +#' @example x = runif(10, 0, 1) +#' mean(x) +#' jackknife(x,mean) +#' +#' @export + +jackknife<-function (x,t) +{ + n=length(x) + jk=rep(NA,n) + + for (i in 1:n) + { + jk[i]=t(x[-i]) + jkest=mean(jk) + jkvar=(n-1)/n*sum((jk-jkest)^2) + jkbias=(n-1)*(jkest-t(x)) + jkbiascorr=n*t(x)-(n-1)*jkest + } + list(est=t(x), jkest=jkest, jkvar=jkvar, jkbias=jkbias, jkbiascorr=jkbiascorr) +} From d56c5104fd853dcbac8c45209b4bb4ba9d53f874 Mon Sep 17 00:00:00 2001 From: dcaff Date: Thu, 25 Apr 2013 11:52:28 -0600 Subject: [PATCH 2/2] updated documentation --- R/em.mixnorm.R | 1 + 1 file changed, 1 insertion(+) diff --git a/R/em.mixnorm.R b/R/em.mixnorm.R index 98264e3..483cc03 100644 --- a/R/em.mixnorm.R +++ b/R/em.mixnorm.R @@ -5,6 +5,7 @@ #' #' @author Tyler Hunt \email{tyler@@psychoanalytix.com} #' @export + em.mixnorm <- function (x,k){ p = rep(1/k,k)