[Returnanalytics-commits] r3142 - in pkg/Meucci: R demo man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Sep 19 11:43:24 CEST 2013
Author: xavierv
Date: 2013-09-19 11:43:24 +0200 (Thu, 19 Sep 2013)
New Revision: 3142
Modified:
pkg/Meucci/R/RandNormalInverseWishart.R
pkg/Meucci/demo/S_AnalyzeNormalInverseWishart.R
pkg/Meucci/demo/S_CorrelationPriorUniform.R
pkg/Meucci/demo/S_MarkovChainMonteCarlo.R
pkg/Meucci/man/RandNormalInverseWishart.Rd
Log:
- updated documentation for chapter 7 demo scripts and its functions
Modified: pkg/Meucci/R/RandNormalInverseWishart.R
===================================================================
--- pkg/Meucci/R/RandNormalInverseWishart.R 2013-09-19 08:29:50 UTC (rev 3141)
+++ pkg/Meucci/R/RandNormalInverseWishart.R 2013-09-19 09:43:24 UTC (rev 3142)
@@ -1,20 +1,21 @@
-
-#' Generates a multivariate i.i.d. sample of lenght J from the normal-inverse-Wishart distribution, as described in
+#' @title Generates a multivariate i.i.d. sample of lenght J from the normal-inverse-Wishart distribution.
+#'
+#' @description Generates a multivariate i.i.d. sample of lenght J from the normal-inverse-Wishart distribution, as described in
#' A. Meucci "Risk and Asset Allocation", Springer, 2005.
#'
-#' @param Mu_0 : [vector]
-#' @param T_0 : [scalar]
-#' @param Sigma_0 : [matrix]
-#' @param nu_0 : [scalar]
-#' @param J : [scalar]
+#' @param Mu_0 [vector] location parameter.
+#' @param T_0 [scalar] number of observations.
+#' @param Sigma_0 [matrix] scatter parameter.
+#' @param nu_0 [scalar] degrees of freedom.
+#' @param J [scalar] number of simulations to compute.
#'
-#' @return Mu : [vector]
-#' @return Sigma : [matrix]
-#' @return InvSigma : [matrix]
+#' @return Mu [vector] location parameter from the normal-inverse-Wishart distribution.
+#' @return Sigma [matrix] dispersion parameter from the normal-inverse-Wishart distribution.
+#' @return InvSigma [matrix] inverse of the dispersion parameter from the normal-inverse-Wishart distribution.
#'
-#' @note
-#' Mu|Sigma ~ N(Mu_0,Sigma/T_0)
-#' inv(Sigma) ~ W(Nu_0,inv(Sigma_0)/Nu_0)
+#' @note
+#' \deqn{\mu\| \Sigma \sim N(\mu_{0}, \frac{\Sigma}{T_{0}}) }{Mu|Sigma ~ N(Mu_0,Sigma/T_0)}
+#' \deqn{\Sigma^{-1} \sim W(\nu_{0},\frac{\Sigma_{0}^{-1}}{\nu_{0}})}{inv(Sigma) ~ W(Nu_0,inv(Sigma_0)/Nu_0)}
#'
#' @references
#' A. Meucci - "Exercises in Advanced Risk and Portfolio Management" \url{http://symmys.com/node/170}.
Modified: pkg/Meucci/demo/S_AnalyzeNormalInverseWishart.R
===================================================================
--- pkg/Meucci/demo/S_AnalyzeNormalInverseWishart.R 2013-09-19 08:29:50 UTC (rev 3141)
+++ pkg/Meucci/demo/S_AnalyzeNormalInverseWishart.R 2013-09-19 09:43:24 UTC (rev 3142)
@@ -4,7 +4,9 @@
#' Described in A. Meucci,"Risk and Asset Allocation",Springer, 2005, Chapter 7.
#'
#' @references
-#' A. Meucci - "Exercises in Advanced Risk and Portfolio Management" \url{http://symmys.com/node/170}.
+#' A. Meucci - "Exercises in Advanced Risk and Portfolio Management" \url{http://symmys.com/node/170},
+#' "E 282 - Bayesian: normal-inverse-Wishart posterior".
+#'
#' See Meucci's script for "S_AnalyzeNormalInverseWishart.m"
#
#' @author Xavier Valls \email{flamejat@@gmail.com}
Modified: pkg/Meucci/demo/S_CorrelationPriorUniform.R
===================================================================
--- pkg/Meucci/demo/S_CorrelationPriorUniform.R 2013-09-19 08:29:50 UTC (rev 3141)
+++ pkg/Meucci/demo/S_CorrelationPriorUniform.R 2013-09-19 09:43:24 UTC (rev 3142)
@@ -3,7 +3,9 @@
#' Chapter 7.
#'
#' @references
-#' A. Meucci - "Exercises in Advanced Risk and Portfolio Management" \url{http://symmys.com/node/170}.
+#' A. Meucci - "Exercises in Advanced Risk and Portfolio Management" \url{http://symmys.com/node/170},
+#' "E 281 - Bayesian: prior on correlation".
+#'
#' See Meucci's script for "S_CorrelationPriorUniform.m"
#
#' @author Xavier Valls \email{flamejat@@gmail.com}
@@ -18,13 +20,13 @@
### Compute correlations in all scenarios
CorrsAsTensor = array(0, dim = c(J,N,N) );
Eigs = NULL;
-j = 1;
+j = 1;
while( j < J )
{
- C = 2 * matrix( runif(K), 1, K ) - 1;
+ C = 2 * matrix( runif(K), 1, K ) - 1;
Corr = diag( 1, N );
- k = 0;
+ k = 0;
for( n in 1 : ( N - 1 ) )
{
for( m in ( n + 1 ) : N )
@@ -58,7 +60,7 @@
#####################################################################################################################
### Plots
# univariate marginals
-K = nrow( CorrsAsEntries );
+K = nrow( CorrsAsEntries );
Nbins = round( 5 * log( J ) );
for( k in 1 : K )
{
Modified: pkg/Meucci/demo/S_MarkovChainMonteCarlo.R
===================================================================
--- pkg/Meucci/demo/S_MarkovChainMonteCarlo.R 2013-09-19 08:29:50 UTC (rev 3141)
+++ pkg/Meucci/demo/S_MarkovChainMonteCarlo.R 2013-09-19 09:43:24 UTC (rev 3142)
@@ -2,7 +2,9 @@
#' Springer, 2005, Chapter 7.
#'
#' @references
-#' A. Meucci - "Exercises in Advanced Risk and Portfolio Management" \url{http://symmys.com/node/170}.
+#' A. Meucci - "Exercises in Advanced Risk and Portfolio Management" \url{http://symmys.com/node/170},
+#' "E 280 - Markov chain Monte Carlo".
+#'
#' See Meucci's script for "S_MarkovChainMonteCarlo.m"
#
#' @author Xavier Valls \email{flamejat@@gmail.com}
@@ -19,9 +21,10 @@
##################################################################################################################
### Set up MH algorithm
nSim = 10000;
-xt = matrix( NaN, nSim, 1);
+xt = matrix( NaN, nSim, 1);
+nacc = 0;
xt[ 1 ] = 0;
-nacc = 0;
+
for( i in 2 : nSim )
{
# normal candidate
@@ -30,12 +33,13 @@
f1 = kernel( r );
# kernel at past
f2 = kernel( xt[ i-1 ] );
- prob = f1 / f2;
+
+ prob = f1 / f2;
xt[ i ] = xt[ i-1 ];
if( prob > 1 || runif(1) > (1 - prob) )
{
xt[ i ] = r;
- nacc = nacc + 1;
+ nacc = nacc + 1;
}
}
##################################################################################################################
Modified: pkg/Meucci/man/RandNormalInverseWishart.Rd
===================================================================
--- pkg/Meucci/man/RandNormalInverseWishart.Rd 2013-09-19 08:29:50 UTC (rev 3141)
+++ pkg/Meucci/man/RandNormalInverseWishart.Rd 2013-09-19 09:43:24 UTC (rev 3142)
@@ -1,27 +1,29 @@
\name{RandNormalInverseWishart}
\alias{RandNormalInverseWishart}
-\title{Generates a multivariate i.i.d. sample of lenght J from the normal-inverse-Wishart distribution, as described in
-A. Meucci "Risk and Asset Allocation", Springer, 2005.}
+\title{Generates a multivariate i.i.d. sample of lenght J from the normal-inverse-Wishart distribution.}
\usage{
RandNormalInverseWishart(Mu_0, T_0, Sigma_0, nu_0, J)
}
\arguments{
- \item{Mu_0}{: [vector]}
+ \item{Mu_0}{[vector] location parameter.}
- \item{T_0}{: [scalar]}
+ \item{T_0}{[scalar] number of observations.}
- \item{Sigma_0}{: [matrix]}
+ \item{Sigma_0}{[matrix] scatter parameter.}
- \item{nu_0}{: [scalar]}
+ \item{nu_0}{[scalar] degrees of freedom.}
- \item{J}{: [scalar]}
+ \item{J}{[scalar] number of simulations to compute.}
}
\value{
- Mu : [vector]
+ Mu [vector] location parameter from the
+ normal-inverse-Wishart distribution.
- Sigma : [matrix]
+ Sigma [matrix] dispersion parameter from the
+ normal-inverse-Wishart distribution.
- InvSigma : [matrix]
+ InvSigma [matrix] inverse of the dispersion parameter
+ from the normal-inverse-Wishart distribution.
}
\description{
Generates a multivariate i.i.d. sample of lenght J from
@@ -29,8 +31,10 @@
A. Meucci "Risk and Asset Allocation", Springer, 2005.
}
\note{
- Mu|Sigma ~ N(Mu_0,Sigma/T_0) inv(Sigma) ~
- W(Nu_0,inv(Sigma_0)/Nu_0)
+ \deqn{\mu\| \Sigma \sim N(\mu_{0}, \frac{\Sigma}{T_{0}})
+ }{Mu|Sigma ~ N(Mu_0,Sigma/T_0)} \deqn{\Sigma^{-1} \sim
+ W(\nu_{0},\frac{\Sigma_{0}^{-1}}{\nu_{0}})}{inv(Sigma) ~
+ W(Nu_0,inv(Sigma_0)/Nu_0)}
}
\author{
Xavier Valls \email{flamejat at gmail.com}
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