[Returnanalytics-commits] r3066 - in pkg/PerformanceAnalytics/sandbox/pulkit: . R man src
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Sep 12 03:05:37 CEST 2013
Author: pulkit
Date: 2013-09-12 03:05:36 +0200 (Thu, 12 Sep 2013)
New Revision: 3066
Added:
pkg/PerformanceAnalytics/sandbox/pulkit/R/ExtremeDrawdown.R
pkg/PerformanceAnalytics/sandbox/pulkit/R/gpdmle.R
pkg/PerformanceAnalytics/sandbox/pulkit/man/DrawdownGPD.Rd
pkg/PerformanceAnalytics/sandbox/pulkit/src/gpd.c
Modified:
pkg/PerformanceAnalytics/sandbox/pulkit/DESCRIPTION
pkg/PerformanceAnalytics/sandbox/pulkit/NAMESPACE
pkg/PerformanceAnalytics/sandbox/pulkit/R/chart.Penance.R
pkg/PerformanceAnalytics/sandbox/pulkit/R/chart.REDD.R
pkg/PerformanceAnalytics/sandbox/pulkit/R/redd.R
pkg/PerformanceAnalytics/sandbox/pulkit/man/chart.Penance.Rd
pkg/PerformanceAnalytics/sandbox/pulkit/man/rollDrawdown.Rd
pkg/PerformanceAnalytics/sandbox/pulkit/src/moment.c
Log:
GPD files added
Modified: pkg/PerformanceAnalytics/sandbox/pulkit/DESCRIPTION
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/DESCRIPTION 2013-09-11 22:05:46 UTC (rev 3065)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/DESCRIPTION 2013-09-12 01:05:36 UTC (rev 3066)
@@ -49,3 +49,5 @@
'psr_python.R'
'ret.R'
'Penance.R'
+ 'ExtremeDrawdown.R'
+ 'gpdmle.R'
Modified: pkg/PerformanceAnalytics/sandbox/pulkit/NAMESPACE
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/NAMESPACE 2013-09-11 22:05:46 UTC (rev 3065)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/NAMESPACE 2013-09-12 01:05:36 UTC (rev 3066)
@@ -7,6 +7,7 @@
export(chart.Penance)
export(chart.REDD)
export(chart.SRIndifference)
+export(DrawdownGPD)
export(EconomicDrawdown)
export(EDDCOPS)
export(golden_section)
Added: pkg/PerformanceAnalytics/sandbox/pulkit/R/ExtremeDrawdown.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/R/ExtremeDrawdown.R (rev 0)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/R/ExtremeDrawdown.R 2013-09-12 01:05:36 UTC (rev 3066)
@@ -0,0 +1,80 @@
+#'@title
+#'Modelling Drawdown using Extreme Value Theory
+#'
+#"@description
+#'It has been shown empirically that Drawdowns can be modelled using Modified Generalized Pareto
+#'distribution(MGPD), Generalized Pareto Distribution(GPD) and other particular cases of MGPD such
+#'as weibull distribution \eqn{MGPD(\gamma,0,\psi)} and unit exponential distribution\eqn{MGPD(1,0,\psi)}
+#'
+#' Modified Generalized Pareto Distribution is given by the following formula
+#'
+#' \deqn{
+#' G_{\eta}(m) = \begin{array}{l} 1-(1+\eta\frac{m^\gamma}{\psi})^(-1/\eta), if \eta \neq 0 \\ 1- e^{-frac{m^\gamma}{\psi}}, if \eta = 0,\end{array}}
+#'
+#' Here \eqn{\gamma{\epsilon}R} is the modifying parameter. When \eqn{\gamma<1} the corresponding densities are
+#' strictly decreasing with heavier tail; the GDP is recovered by setting \eqn{\gamma = 1} .\eqn{\gamma \textgreater 1}
+#'
+#' The GDP is given by the following equation. \eqn{MGPD(1,\eta,\psi)}
+#'
+#'\deqn{G_{\eta}(m) = \begin{array}{l} 1-(1+\eta\frac{m}{\psi})^(-1/\eta), if \eta \neq 0 \\ 1- e^{-frac{m}{\psi}}, if \eta = 0,\end{array}}
+#'
+#' The weibull distribution is given by the following equation \eqn{MGPD(\gamma,0,\psi)}
+#'
+#'\deqn{G(m) = 1- e^{-frac{m^\gamma}{\psi}}}
+#'
+#'In this function generalized Pareto distribution has been covered. This function can be
+#'expanded in the future to include more Extreme Value distributions as the literature on such distribution
+#'matures in the future.
+#'
+#' @param R an xts, vector, matrix, data frame, timeSeries or zoo object of asset return
+#' @param threshold The threshold beyond which the drawdowns have to be modelled
+#'
+#'
+#'@references
+#'Mendes, Beatriz V.M. and Leal, Ricardo P.C., Maximum Drawdown: Models and Applications (November 2003).
+#'Coppead Working Paper Series No. 359.Available at SSRN: http://ssrn.com/abstract=477322 or http://dx.doi.org/10.2139/ssrn.477322.
+#'
+#'@examples
+#'data(edhec)
+#'DrawdownGPD(edhec)
+#'data(managers)
+#'DrawdownGPD(managers[,1:9],0.95)
+#'
+#'@export
+DrawdownGPD<-function(R,threshold=0.90){
+ x = checkData(R)
+ columns = ncol(R)
+ columnnames = colnames(R)
+ gpdfit<-function(data,threshold){
+ gpd_fit = gpd(as.vector(data),as.vector(threshold))
+ result = list(shape = gpd_fit$param[2],scale = gpd_fit$param[1])
+ return(result)
+ }
+ for(column in 1:columns){
+ dr = -Drawdowns(R[,column])
+ thresh = quantile(na.omit(dr),threshold)
+ column.parameters = gpdfit(dr,thresh)
+ if(column == 1){
+ shape = column.parameters$shape
+ scale = column.parameters$scale
+ }
+ else {
+ scale = c(scale, column.parameters$scale)
+ shape = c(shape, column.parameters$shape)
+ }
+ }
+ parameters = rbind(scale,shape)
+ colnames(parameters) = columnnames
+ parameters = reclass(parameters, x)
+ rownames(parameters)=c("scale","shape")
+ return(parameters)
+}
+
+
+
+
+
+
+
+
+
Modified: pkg/PerformanceAnalytics/sandbox/pulkit/R/chart.Penance.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/R/chart.Penance.R 2013-09-11 22:05:46 UTC (rev 3065)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/R/chart.Penance.R 2013-09-12 01:05:36 UTC (rev 3066)
@@ -42,7 +42,7 @@
#'
#'@export
-chart.Penance<-function(R,confidence,type=c("ar","normal"),reference.grid = TRUE,main=NULL,ylab = NULL,xlab = NULL,element.color="darkgrey",lwd = 2,pch = 1,cex = 1,cex.axis=0.8,cex.lab = 1,cex.main = 1,xlim = NULL,ylim = NULL,...){
+chart.Penance<-function(R,confidence=0.95,type=c("ar","normal"),reference.grid = TRUE,main=NULL,ylab = NULL,xlab = NULL,element.color="darkgrey",lwd = 2,pch = 1,cex = 1,cex.axis=0.8,cex.lab = 1,cex.main = 1,xlim = NULL,ylim = NULL,...){
# DESCRIPTION:
# Draws the scatter plot of Phi vs Penance.
Modified: pkg/PerformanceAnalytics/sandbox/pulkit/R/chart.REDD.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/R/chart.REDD.R 2013-09-11 22:05:46 UTC (rev 3065)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/R/chart.REDD.R 2013-09-12 01:05:36 UTC (rev 3066)
@@ -9,7 +9,9 @@
#'@param rf risk free rate can be vector such as government security rate of return
#'@param h lookback period
#'@param geometric utilize geometric chaining (TRUE) or simple/arithmetic chaining(FALSE) to aggregate returns, default is TRUE.
-#'@param legend.loc set the legend.loc, as in \code{\link{plot}}
+#' @param legend.loc places a legend into one of nine locations on the chart:
+#' bottomright, bottom, bottomleft, left, topleft, top, topright, right, or
+#' center.
#'@param colorset set the colorset label, as in \code{\link{plot}}
#'@param \dots any other variable
#'@author Pulkit Mehrotra
@@ -19,8 +21,9 @@
#'Control Maximum Drawdown - The Case of Risk Based Dynamic Asset Allocation (February 25, 2012)
#'@examples
#'data(edhec)
-#'chart.REDD(edhec,0.08,20)
-#'
+#'chart.REDD(edhec,0.08,20,legend.loc = "topleft")
+#'data(managers)
+#'chart.REDD(managers,0.08,20,legend.loc = "topleft")
#'@export
chart.REDD<-function(R,rf,h, geometric = TRUE,legend.loc = NULL, colorset = (1:12),...)
@@ -34,7 +37,7 @@
# free return(rf) and the lookback period(h) is taken as the input.
- rolldrawdown = rollDrawdown(R,geometric = TRUE,weights = NULL,rf,h)
+ rolldrawdown = rollDrawdown(R,geometric = TRUE,rf,h)
chart.TimeSeries(rolldrawdown, colorset = colorset, legend.loc = legend.loc, ...)
}
Added: pkg/PerformanceAnalytics/sandbox/pulkit/R/gpdmle.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/R/gpdmle.R (rev 0)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/R/gpdmle.R 2013-09-12 01:05:36 UTC (rev 3066)
@@ -0,0 +1,172 @@
+## This function comes from the package "POT" . The gpd function
+## corresponds to the gpdmle function. So, I'm very gratefull to Mathieu Ribatet.
+#'@useDynLib noniid.pm
+gpd <- function(x, threshold, start, ...,
+ std.err.type = "observed", corr = FALSE,
+ method = "BFGS", warn.inf = TRUE){
+
+ if (all(c("observed", "expected", "none") != std.err.type))
+ stop("``std.err.type'' must be one of 'observed', 'expected' or 'none'")
+
+ nlpot <- function(scale, shape) {
+ -.C("gpdlik", exceed, nat, threshold, scale,
+ shape, dns = double(1))$dns
+ }
+
+ nn <- length(x)
+
+ threshold <- rep(threshold, length.out = nn)
+
+ high <- (x > threshold) & !is.na(x)
+ threshold <- as.double(threshold[high])
+ exceed <- as.double(x[high])
+ nat <- length(exceed)
+
+ if(!nat) stop("no data above threshold")
+
+ pat <- nat/nn
+ param <- c("scale", "shape")
+
+ if(missing(start)) {
+
+ start <- list(scale = 0, shape = 0)
+ start$scale <- mean(exceed) - min(threshold)
+
+ start <- start[!(param %in% names(list(...)))]
+
+ }
+
+ if(!is.list(start))
+ stop("`start' must be a named list")
+
+ if(!length(start))
+ stop("there are no parameters left to maximize over")
+
+ nm <- names(start)
+ l <- length(nm)
+ f <- formals(nlpot)
+ names(f) <- param
+ m <- match(nm, param)
+
+ if(any(is.na(m)))
+ stop("`start' specifies unknown arguments")
+
+ formals(nlpot) <- c(f[m], f[-m])
+ nllh <- function(p, ...) nlpot(p, ...)
+
+ if(l > 1)
+ body(nllh) <- parse(text = paste("nlpot(", paste("p[",1:l,
+ "]", collapse = ", "), ", ...)"))
+
+ fixed.param <- list(...)[names(list(...)) %in% param]
+
+ if(any(!(param %in% c(nm,names(fixed.param)))))
+ stop("unspecified parameters")
+
+ start.arg <- c(list(p = unlist(start)), fixed.param)
+ if( warn.inf && do.call("nllh", start.arg) == 1e6 )
+ warning("negative log-likelihood is infinite at starting values")
+
+ opt <- optim(start, nllh, hessian = TRUE, ..., method = method)
+
+ if ((opt$convergence != 0) || (opt$value == 1e6)) {
+ warning("optimization may not have succeeded")
+ if(opt$convergence == 1) opt$convergence <- "iteration limit reached"
+ }
+
+ else opt$convergence <- "successful"
+
+ if (std.err.type != "none"){
+
+ tol <- .Machine$double.eps^0.5
+
+ if(std.err.type == "observed") {
+
+ var.cov <- qr(opt$hessian, tol = tol)
+ if(var.cov$rank != ncol(var.cov$qr)){
+ warning("observed information matrix is singular; passing std.err.type to ``expected''")
+ obs.fish <- FALSE
+ return
+ }
+
+ if (std.err.type == "observed"){
+ var.cov <- try(solve(var.cov, tol = tol), silent = TRUE)
+
+ if(!is.matrix(var.cov)){
+ warning("observed information matrix is singular; passing std.err.type to ''none''")
+ std.err.type <- "expected"
+ return
+ }
+
+ else{
+ std.err <- diag(var.cov)
+ if(any(std.err <= 0)){
+ warning("observed information matrix is singular; passing std.err.type to ``expected''")
+ std.err.type <- "expected"
+ return
+ }
+
+ std.err <- sqrt(std.err)
+
+ if(corr) {
+ .mat <- diag(1/std.err, nrow = length(std.err))
+ corr.mat <- structure(.mat %*% var.cov %*% .mat, dimnames = list(nm,nm))
+ diag(corr.mat) <- rep(1, length(std.err))
+ }
+ else {
+ corr.mat <- NULL
+ }
+ }
+ }
+ }
+
+ if (std.err.type == "expected"){
+
+ shape <- opt$par[2]
+ scale <- opt$par[1]
+ a22 <- 2/((1+shape)*(1+2*shape))
+ a12 <- 1/(scale*(1+shape)*(1+2*shape))
+ a11 <- 1/((scale^2)*(1+2*shape))
+ ##Expected Matix of Information of Fisher
+ expFisher <- nat * matrix(c(a11,a12,a12,a22),nrow=2)
+
+ expFisher <- qr(expFisher, tol = tol)
+ var.cov <- solve(expFisher, tol = tol)
+ std.err <- sqrt(diag(var.cov))
+
+ if(corr) {
+ .mat <- diag(1/std.err, nrow = length(std.err))
+ corr.mat <- structure(.mat %*% var.cov %*% .mat, dimnames = list(nm,nm))
+ diag(corr.mat) <- rep(1, length(std.err))
+ }
+ else
+ corr.mat <- NULL
+ }
+
+ colnames(var.cov) <- nm
+ rownames(var.cov) <- nm
+ names(std.err) <- nm
+ }
+
+ else{
+ std.err <- std.err.type <- corr.mat <- NULL
+ var.cov <- NULL
+ }
+
+
+ param <- c(opt$par, unlist(fixed.param))
+ scale <- param["scale"]
+
+ var.thresh <- !all(threshold == threshold[1])
+
+ if (!var.thresh)
+ threshold <- threshold[1]
+
+ list(fitted.values = opt$par, std.err = std.err, std.err.type = std.err.type,
+ var.cov = var.cov, fixed = unlist(fixed.param), param = param,
+ deviance = 2*opt$value, corr = corr.mat, convergence = opt$convergence,
+ counts = opt$counts, message = opt$message, threshold = threshold,
+ nat = nat, pat = pat, data = x, exceed = exceed, scale = scale,
+ var.thresh = var.thresh, est = "MLE", logLik = -opt$value,
+ opt.value = opt$value, hessian = opt$hessian)
+}
Modified: pkg/PerformanceAnalytics/sandbox/pulkit/R/redd.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/R/redd.R 2013-09-11 22:05:46 UTC (rev 3065)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/R/redd.R 2013-09-12 01:05:36 UTC (rev 3066)
@@ -27,7 +27,8 @@
#'@examples
#'data(edhec)
#'rollDrawdown(edhec,0.08,100)
-#'
+#'data(managers)
+#'rollDrawdown(managers[,1:9],managers[,10],10)
#' @export
rollDrawdown<-function(R,Rf,h, geometric = TRUE,...)
{
Added: pkg/PerformanceAnalytics/sandbox/pulkit/man/DrawdownGPD.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/man/DrawdownGPD.Rd (rev 0)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/man/DrawdownGPD.Rd 2013-09-12 01:05:36 UTC (rev 3066)
@@ -0,0 +1,91 @@
+\name{DrawdownGPD}
+\alias{DrawdownGPD}
+\title{Modelling Drawdown using Extreme Value Theory
+
+It has been shown empirically that Drawdowns can be modelled using Modified Generalized Pareto
+distribution(MGPD), Generalized Pareto Distribution(GPD) and other particular cases of MGPD such
+as weibull distribution \eqn{MGPD(\gamma,0,\psi)} and unit exponential distribution\eqn{MGPD(1,0,\psi)}
+
+Modified Generalized Pareto Distribution is given by the following formula
+
+\deqn{
+G_{\eta}(m) = \begin{array}{l} 1-(1+\eta\frac{m^\gamma}{\psi})^(-1/\eta), if \eta \neq 0 \\ 1- e^{-frac{m^\gamma}{\psi}}, if \eta = 0,\end{array}}
+
+Here \eqn{\gamma{\epsilon}R} is the modifying parameter. When \eqn{\gamma<1} the corresponding densities are
+strictly decreasing with heavier tail; the GDP is recovered by setting \eqn{\gamma = 1} .\eqn{\gamma \textgreater 1}
+
+The GDP is given by the following equation. \eqn{MGPD(1,\eta,\psi)}
+
+\deqn{G_{\eta}(m) = \begin{array}{l} 1-(1+\eta\frac{m}{\psi})^(-1/\eta), if \eta \neq 0 \\ 1- e^{-frac{m}{\psi}}, if \eta = 0,\end{array}}
+
+The weibull distribution is given by the following equation \eqn{MGPD(\gamma,0,\psi)}
+
+\deqn{G(m) = 1- e^{-frac{m^\gamma}{\psi}}}
+
+In this function generalized Pareto distribution has been covered. This function can be
+expanded in the future to include more Extreme Value distributions as the literature on such distribution
+matures in the future.}
+\usage{
+ DrawdownGPD(R, threshold = 0.9)
+}
+\arguments{
+ \item{R}{an xts, vector, matrix, data frame, timeSeries
+ or zoo object of asset return}
+
+ \item{threshold}{The threshold beyond which the drawdowns
+ have to be modelled}
+}
+\description{
+ Modelling Drawdown using Extreme Value Theory
+
+ It has been shown empirically that Drawdowns can be
+ modelled using Modified Generalized Pareto
+ distribution(MGPD), Generalized Pareto Distribution(GPD)
+ and other particular cases of MGPD such as weibull
+ distribution \eqn{MGPD(\gamma,0,\psi)} and unit
+ exponential distribution\eqn{MGPD(1,0,\psi)}
+
+ Modified Generalized Pareto Distribution is given by the
+ following formula
+
+ \deqn{ G_{\eta}(m) = \begin{array}{l}
+ 1-(1+\eta\frac{m^\gamma}{\psi})^(-1/\eta), if \eta \neq 0
+ \\ 1- e^{-frac{m^\gamma}{\psi}}, if \eta = 0,\end{array}}
+
+ Here \eqn{\gamma{\epsilon}R} is the modifying parameter.
+ When \eqn{\gamma<1} the corresponding densities are
+ strictly decreasing with heavier tail; the GDP is
+ recovered by setting \eqn{\gamma = 1} .\eqn{\gamma
+ \textgreater 1}
+
+ The GDP is given by the following equation.
+ \eqn{MGPD(1,\eta,\psi)}
+
+ \deqn{G_{\eta}(m) = \begin{array}{l}
+ 1-(1+\eta\frac{m}{\psi})^(-1/\eta), if \eta \neq 0 \\ 1-
+ e^{-frac{m}{\psi}}, if \eta = 0,\end{array}}
+
+ The weibull distribution is given by the following
+ equation \eqn{MGPD(\gamma,0,\psi)}
+
+ \deqn{G(m) = 1- e^{-frac{m^\gamma}{\psi}}}
+
+ In this function generalized Pareto distribution has been
+ covered. This function can be expanded in the future to
+ include more Extreme Value distributions as the
+ literature on such distribution matures in the future.
+}
+\examples{
+data(edhec)
+DrawdownGPD(edhec)
+data(managers)
+DrawdownGPD(managers[,1:9],0.95)
+}
+\references{
+ Mendes, Beatriz V.M. and Leal, Ricardo P.C., Maximum
+ Drawdown: Models and Applications (November 2003).
+ Coppead Working Paper Series No. 359.Available at SSRN:
+ http://ssrn.com/abstract=477322 or
+ http://dx.doi.org/10.2139/ssrn.477322.
+}
+
Modified: pkg/PerformanceAnalytics/sandbox/pulkit/man/chart.Penance.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/man/chart.Penance.Rd 2013-09-11 22:05:46 UTC (rev 3065)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/man/chart.Penance.Rd 2013-09-12 01:05:36 UTC (rev 3066)
@@ -2,11 +2,12 @@
\alias{chart.Penance}
\title{Penance vs phi plot}
\usage{
- chart.Penance(R, confidence, type = c("ar", "normal"),
- reference.grid = TRUE, main = NULL, ylab = NULL,
- xlab = NULL, element.color = "darkgrey", lwd = 2,
- pch = 1, cex = 1, cex.axis = 0.8, cex.lab = 1,
- cex.main = 1, xlim = NULL, ylim = NULL, ...)
+ chart.Penance(R, confidence = 0.95,
+ type = c("ar", "normal"), reference.grid = TRUE,
+ main = NULL, ylab = NULL, xlab = NULL,
+ element.color = "darkgrey", lwd = 2, pch = 1, cex = 1,
+ cex.axis = 0.8, cex.lab = 1, cex.main = 1, xlim = NULL,
+ ylim = NULL, ...)
}
\arguments{
\item{R}{an xts, vector, matrix, data frame, timeSeries
Modified: pkg/PerformanceAnalytics/sandbox/pulkit/man/rollDrawdown.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/man/rollDrawdown.Rd 2013-09-11 22:05:46 UTC (rev 3065)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/man/rollDrawdown.Rd 2013-09-12 01:05:36 UTC (rev 3066)
@@ -37,6 +37,8 @@
\examples{
data(edhec)
rollDrawdown(edhec,0.08,100)
+data(managers)
+rollDrawdown(managers[,1:9],managers[,10],10)
}
\author{
Pulkit Mehrotra
Added: pkg/PerformanceAnalytics/sandbox/pulkit/src/gpd.c
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/src/gpd.c (rev 0)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/src/gpd.c 2013-09-12 01:05:36 UTC (rev 3066)
@@ -0,0 +1,41 @@
+#include<R.h>
+#include<Rinternals.h>
+#include<Rmath.h>
+
+
+void gpdlik(double *data, int *n, double *loc, double *scale,
+ double *shape, double *dns)
+{
+ int i;
+ double *dvec;
+
+ dvec = (double *)R_alloc(*n, sizeof(double));
+
+ if(*scale <= 0) {
+ *dns = -1e6;
+ return;
+ }
+
+ for(i=0;i<*n;i++) {
+ data[i] = (data[i] - loc[i]) / *scale;
+ if (data[i] <= 0) {
+ *dns = -1e6;
+ return;
+ }
+ if(fabs(*shape) <= 1e-6){
+ *shape = 0;
+ dvec[i] = -log(*scale) - data[i];
+ }
+ else {
+ data[i] = 1 + *shape * data[i];
+ if(data[i] <= 0) {
+ *dns = -1e6;
+ return;
+ }
+ dvec[i] = -log(*scale) - (1 / *shape + 1) * log(data[i]);
+ }
+ }
+
+ for(i=0;i<*n;i++)
+ *dns = *dns + dvec[i];
+}
Modified: pkg/PerformanceAnalytics/sandbox/pulkit/src/moment.c
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/src/moment.c 2013-09-11 22:05:46 UTC (rev 3065)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/src/moment.c 2013-09-12 01:05:36 UTC (rev 3066)
@@ -56,5 +56,4 @@
return Rsum;
}
-
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