[Returnanalytics-commits] r2145 - in pkg/PerformanceAnalytics/sandbox/Meucci: R man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Wed Jul 11 19:56:30 CEST 2012


Author: braverock
Date: 2012-07-11 19:56:29 +0200 (Wed, 11 Jul 2012)
New Revision: 2145

Removed:
   pkg/PerformanceAnalytics/sandbox/Meucci/man/EfficientFrontier.Rd
Modified:
   pkg/PerformanceAnalytics/sandbox/Meucci/R/DetectOutliersviaMVE.R
   pkg/PerformanceAnalytics/sandbox/Meucci/R/EntropyProg.R
   pkg/PerformanceAnalytics/sandbox/Meucci/R/FullyFlexibleBayesNets.R
   pkg/PerformanceAnalytics/sandbox/Meucci/R/InvariantProjection.R
   pkg/PerformanceAnalytics/sandbox/Meucci/R/Prior2Posterior.R
   pkg/PerformanceAnalytics/sandbox/Meucci/R/RankingInformation.R
   pkg/PerformanceAnalytics/sandbox/Meucci/R/RobustBayesianAllocation.R
   pkg/PerformanceAnalytics/sandbox/Meucci/R/logToArithmeticCovariance.R
   pkg/PerformanceAnalytics/sandbox/Meucci/man/Central2Raw.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/ComputeMVE.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/CondProbViews.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/Cumul2Raw.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/GenerateLogNormalDistribution.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/PartialConfidencePosterior.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/PlotDistributions.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/Prior2Posterior.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Central.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Cumul.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/StackedBarChart.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/Tweak.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/ViewRanking.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/linreturn.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/robustBayesianPortfolioOptimization.Rd
   pkg/PerformanceAnalytics/sandbox/Meucci/man/std.Rd
Log:
- changes to roxygen comments and a few manual edits to .Rd files so documentation will compile, more to do here.


Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/DetectOutliersviaMVE.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/DetectOutliersviaMVE.R	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/DetectOutliersviaMVE.R	2012-07-11 17:56:29 UTC (rev 2145)
@@ -46,28 +46,33 @@
 #' Compute the minimum volume ellipsoid for a given (multi-variate) time-series
 #'
 #' Function computes the minimum volume ellipsoid for a given time series
+#' 
 #' via the expectations-minimization algorithm
-#' The location and scatter parameters that define the ellipsoid are 
-#' multivariate high-breakdown estimators of location and scatter 
-#'
-#' @param  data     a matrix time-series of data. Each row is a observation (date). Each column is an asset
-#' @return list     a list with
-#'      MVE_Location   a numeric with the location parameter of minimum volume ellipsoid
-#'      MVE_Dispersion a numeric with the covariance matrix of the minimum volume ellipsoid
-#' \deqn { w_{t} =  \frac{1}{T} , t = 1,...,T
+#' 
+#' \deqn{ w_{t} =  \frac{1}{T} , t = 1,...,T
 #' \\ m  \equiv \frac{1}{ \sum_{s=1}^T  w_{s} } \sum_{t=1}^T  w_{t}  x_{t}    
 #' \\ S \equiv \sum_{t=1}^T w_{t} \big(x_{t} - m\big) \big(x_{t} - m\big)'
 #' \\ Ma_{t}^{2} \equiv  \big(x-m\big)'  S^{-1}  \big(x-m\big), t=1,...,T 
 #' \\ w_{t}  \mapsto w_{t} Ma_{t}^{2}
 #' \\ U =  \big(x_{1}' -  \hat{E}',...,x_{T}' - \hat{E}' \big)   
 #' \\  \hat{Cov}  \equiv  \frac{1}{T} U'U }
+#' 
+#' The location and scatter parameters that define the ellipsoid are 
+#' multivariate high-breakdown estimators of location and scatter 
+#' 
+#' @param  data     a matrix time-series of data. Each row is a observation (date). Each column is an asset
 #' @author Ram Ahluwalia \email{ram@@wingedfootcapital.com}
+#' @return list     a list with
+#'      MVE_Location   a numeric with the location parameter of minimum volume ellipsoid
+#'      MVE_Dispersion a numeric with the covariance matrix of the minimum volume ellipsoid
+#' 
 #' @references 
-#' \url{http://www.symmys.com/sites/default/files/Risk%20and%20Asset%20Allocation%20-%20Springer%20Quantitative%20Finance%20-%20Estimation.pdf}
+#' \url{http://www.symmys.com/sites/default/files/Risk\%20and\%20Asset\%20Allocation\%20-\%20Springer\%20Quantitative\%20Finance\%20-\%20Estimation.pdf}
 #' See Sec. 4.6.1 of "Risk and Asset Allocation" - Springer (2005), by A. Meucci
 #' for the theory and the routine implemented below
 #' See Meucci script for "ComputeMVE.m"
 #' @export
+#' 
 ComputeMVE = function ( data )
 {
   library( matlab )    

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/EntropyProg.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/EntropyProg.R	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/EntropyProg.R	2012-07-11 17:56:29 UTC (rev 2145)
@@ -31,7 +31,7 @@
 #'      p_                       revised probabilities based on entropy pooling
 #'      optimizationPerformance  a list with status of optimization, value, number of iterations and sum of probabilities.
 #' @export
-#' \deqn { \tilde{p}  \equiv  argmin_{Fx \leq f, Hx  \equiv  h}  \big\{ \sum_1^J  x_{j}  \big(ln \big( x_{j} \big) - ln \big( p_{j} \big) \big)  \big\} 
+#' \deqn{ \tilde{p}  \equiv  argmin_{Fx \leq f, Hx  \equiv  h}  \big\{ \sum_1^J  x_{j}  \big(ln \big( x_{j} \big) - ln \big( p_{j} \big) \big)  \big\} 
 #' \\ \ell  \big(x,  \lambda,  \nu \big)  \equiv  x'  \big(ln \big(x\big) - ln \big(p\big) \big) +   \lambda' \big(Fx - f\big)  +   \nu' \big(Hx - h\big)}
 #' @author Ram Ahluwalia \email{ram@@wingedfootcapital.com}
 #' @references 
@@ -188,13 +188,13 @@
 #' @param S_G   a numeric with the expectation associated with the covariance of the linear combination GX
 #'
 #' @return a list with 
-#'             M_   a numeric vector with the full-confidence posterior distribution of Mu
-#'             S_   a covariance matrix with the full-confidence posterior distribution of Sigma
+#'             M_   a numeric vector with the full-confidence posterior distribution of \Mu
+#'             S_   a covariance matrix with the full-confidence posterior distribution of \Sigma
 #'
 #' @references 
 #' \url{http://www.symmys.com}
 #' \url{http://ssrn.com/abstract=1213325}
-#' \deqn { \tilde{ \mu }  \equiv \mu +  \Sigma  Q'    {\big(Q \Sigma  Q' \big)}^{-1}   \big( \tilde{\mu}_{Q} - Q \mu \big),
+#' \deqn{ \tilde{ \mu }  \equiv \mu +  \Sigma  Q'    {\big(Q \Sigma  Q' \big)}^{-1}   \big( \tilde{\mu}_{Q} - Q \mu \big),
 #' \\ \tilde{ \Sigma } \equiv \Sigma + \Sigma G' \big({\big(G \Sigma  G' \big)}^{-1} \tilde{ \Sigma }_G {\big(G \Sigma  G' \big)}^{-1} - {\big(G \Sigma  G' \big)}^{-1} \big) G \Sigma }
 #' A. Meucci - "Fully Flexible Views: Theory and Practice". See formula (21) and (22) on page 7
 #' See Meucci script Prior2Posterior.m attached to Entropy Pooling Paper
@@ -256,4 +256,4 @@
   barplot( f , x , 1 )
   
   return( list( f = f , x = x ) )
-}
\ No newline at end of file
+}

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/FullyFlexibleBayesNets.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/FullyFlexibleBayesNets.R	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/FullyFlexibleBayesNets.R	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,9 +1,12 @@
-# Input views
-# statement: View(k).Who (e.g. [1 3])= View(k).Equal (e.g. {[2 3] [1 3 5]})
-# optional conditional statement: View(k).Cond_Who (e.g. [2])= View(k).Cond_Equal (e.g. {[1]})
-# amount of stress is quantified as Prob(statement) <= View(k).v if View(k).sgn = 1;
-#                                   Prob(statement) >= View(k).v if View(k).sgn = -1;
-# confidence in stress is quantified in View(k).c in (0,1)
+#' Input conditional views
+#' 
+#' statement: View(k).Who (e.g. [1 3])= View(k).Equal (e.g. {[2 3] [1 3 5]})
+#' optional conditional statement: View(k).Cond_Who (e.g. [2])= View(k).Cond_Equal (e.g. {[1]})
+#' amount of stress is quantified as Prob(statement) <= View(k).v if View(k).sgn = 1;
+#'                                   Prob(statement) >= View(k).v if View(k).sgn = -1;
+#' 
+#' confidence in stress is quantified in View(k).c in (0,1)
+#' 
 #' @param View              TBD
 #' @param X                 TBD
 #'
@@ -11,6 +14,7 @@
 #' @return b                TBD
 #' @return g                TBD
 #' @author Ram Ahluwalia \email{ram@@wingedfootcapital.com}
+#' @export
 CondProbViews = function( View , X ) 
 {    
   # initialize parameters    
@@ -64,6 +68,7 @@
   return( list( A = A , b = b , g = g ) )
 }
 
+#' tweak a matrix
 #' @param   A     matrix A consisting of inequality constraints ( Ax <= b )
 #' @param   b     matrix b consisting of inequality constraint vector b ( Ax <= b )
 #' @param   g     TODO: TBD

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/InvariantProjection.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/InvariantProjection.R	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/InvariantProjection.R	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,11 +1,16 @@
 #' Transforms the first n raw moments into the first n central moments
 #'
-#' step 6 of projection process: compute multi-period central moments. Note the first central moment defined as expectation.
+#' step 6 of projection process: 
+#' 
+#' compute multi-period central moments. 
+#' 
+#' Note the first central moment defined as expectation.
 #'
+#' #' \deqn{\tilde{ \mu } ^ {\big(n\big)} _{X}  \equiv E \big\{ X^{n} \big\},
+#' \\ \mu ^{ \big(n\big) }_{X}  \equiv  \sum_0^{n-1}  \big(-1\big)^{n-k}   \mu ^{n-k}_{X}  \tilde{ \mu }^{k}_{X} +  \tilde{ \mu }_{X}^{n}   }
+#' 
 #' @param  mu_   the raw (multi-period) non-central moment of Y-t
 #' @return mu    (multi-period) central moment of Y-t
-#' \deqn {\tilde{ \mu } ^ {\big(n\big)} _{X}  \equiv E \big\{ X^{n} \big\},
-#' \\ \mu ^{ \big(n\big) }_{X}  \equiv  \sum_0^{n-1}  \big(-1\big)^{n-k}   \mu ^{n-k}_{X}  \tilde{ \mu }^{k}_{X} +  \tilde{ \mu }_{X}^{n}   }
 #' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
 #' @references
 #' A. Meucci - "Exercises in Advanced Risk and Portfolio Management". See page 9
@@ -30,12 +35,20 @@
 
 #' Transforms cumulants of Y-t into raw moments
 #'
-#' step 5 of the projection process: From the cumulants of Y we compute the raw non-central moments of Y
+#' step 5 of the projection process: 
+#' 
+#' From the cumulants of Y we compute the raw non-central moments of Y
+#' 
 #' We do so recursively by the identity in formula (24) which follows from applying (21) and re-arranging terms
 #'
+#' \deqn{ \tilde{ \mu } ^{ \big(n\big) }_{Y} 
+#' \\ \equiv \kappa^{ \big(n\big) }_{Y}  +  \sum_{k=1}^{n-1} %BPremoved $ $^{n-1} 
+#' C_{k-1}  
+#' \\  \kappa_{Y}^{ \big(k\big) }   \tilde{ \mu } ^{n-k}_{Y}  }
+#' 
 #' @param  ka     cumulants of Y
 #' @return mu_    the raw non-central moments of Y
-#' \deqn {\tilde{ \mu } ^{ \big(n\big) }_{Y} \equiv \kappa^{ \big(n\big) }_{Y}  +  \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$  \kappa_{Y}^{ \big(k\big) }   \tilde{ \mu } ^{n-k}_{Y}  }
+#' 
 #' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
 #' @references
 #' A. Meucci - "Annualization and General Projection of Skewness, Kurtosis and All Summary Statistics" - formula (24)
@@ -59,13 +72,16 @@
 #' Transforms raw moments into cumulants
 #'
 #' Step 3 of the projection process: From the non-central moments of X-t, we compute the cumulants. 
+#' 
+#' 
 #' This process follows from the Taylor approximations for any small z and ln(1+x)~x for any small x,
 #' and from the definition of the first cumulant in (17). The we apply recursively the identity
 #' in formula (21). See Kendall and Stuart (1969)
 #'
+#' \deqn{ \kappa^{ \big(n\big) }_{X}   \equiv \tilde{ \mu } ^{ \big(n\big) }_{X} -  \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$  \kappa_{X}^{ \big(k\big) }   \tilde{ \mu } ^{n-k}_{X} }
+#' 
 #' @param mu_       non-central moments of the invariant X-t
 #' @return ka       cumulants of X-t
-#' \deqn { \kappa^{ \big(n\big) }_{X}   \equiv \tilde{ \mu } ^{ \big(n\big) }_{X} -  \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$  \kappa_{X}^{ \big(k\big) }   \tilde{ \mu } ^{n-k}_{X} }
 #' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
 #' @references
 #' A. Meucci - "Annualization and General Projection of Skewness, Kurtosis and All Summary Statistics" - formula (21)
@@ -92,11 +108,13 @@
 #' step 2 of projection process: From the central moments of step 1, we compute the non-central moments. To do so we start
 #' with the first non-central moment and apply recursively an identity (formula 20)
 #'
+#' \deqn{ \tilde{ \mu }^{ \big(1\big) }_{X} \equiv \mu ^{\big(1\big)}_{X}
+#' \\ \tilde{ \mu }^{ \big(n\big) }_{X}  \equiv \mu ^{n}_{X} \sum_{k=0}^{n-1}  \big(-1\big)^{n-k+1}   \mu ^{n-k}_{X}  \tilde{ \mu }^{\big(k\big)}_{X} }
+
 #' @param   mu      a vector of central moments
 #' @return  mu_     a vector of non-central moments
 #' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
-#' \deqn{ \tilde{ \mu }^{ \big(1\big) }_{X} \equiv \mu ^{\big(1\big)}_{X}
-#' \\ \tilde{ \mu }^{ \big(n\big) }_{X}  \equiv \mu ^{n}_{X} \sum_{k=0}^{n-1}  \big(-1\big)^{n-k+1}   \mu ^{n-k}_{X}  \tilde{ \mu }^{\big(k\big)}_{X} }
+#' @references 
 #' A. Meucci - "Exercises in Advanced Risk and Portfolio Management". See page 10.
 #' Symmys site containing original MATLAB source code \url{http://www.symmys.com}
 
@@ -154,7 +172,7 @@
 
 #' Calculates the population standard deviation
 #'
-#' Calculates the population standard deviaiton dividing by 'n' instead of 'n-1' equivalent to Matlab
+#' Calculates the population standard deviation dividing by 'n' instead of 'n-1' equivalent to Matlab
 #'
 #' @param   x    a generic numeric vector
 #' @return  std  a numeric with the population standard deviaiton of the generic numeric
@@ -162,7 +180,9 @@
 #' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
 std = function( x ) { ( sum( ( x - mean( x ) ) ^ 2 ) / length( x ) ) ^.5 }
 
-#' Generate arbitrary distribution of a shifted-lognormal invariant: X-t + a ~ LogN(m,s^2) (formula 14)
+#' Generate arbitrary distribution of a shifted-lognormal invariant
+#' 
+#' %\deqn{X-t + a ~ LogN(m,s^2)} (formula 14)
 #'
 #' @param   J    a numeric with the number of scenarios
 #' @param   a    a numeric with the location shift parameter. Mean of distribution will be exp(a)
@@ -178,4 +198,5 @@
   X = a + exp( m + s * Z ) # a Jx1 numeric vector
   
   return( X = X )
-}
\ No newline at end of file
+}
+

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/Prior2Posterior.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/Prior2Posterior.R	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/Prior2Posterior.R	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,3 +1,4 @@
+#' plot dists
 #' @param X 
 #' @param p 
 #' @param Mu 

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/RankingInformation.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/RankingInformation.R	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/RankingInformation.R	2012-07-11 17:56:29 UTC (rev 2145)
@@ -17,6 +17,7 @@
   return( p )
 }
 
+#' view the rankings
 #' @param  Lower    a vector of indexes indicating which column is lower than the corresponding column number in Upper
 #' @param  Upper    a vector of indexes indicating which column is lower than the corresponding column number in Upper
 #' @export EntropyProg
@@ -48,7 +49,7 @@
   return( p_ )
 }
 
-#' Generates an efficient frontier based on the Meucci's Ranking Information version with the following inputs
+#' Generates an efficient frontier based on Meucci's Ranking Information version with the following inputs
 #' @param  X             a matrix with the joint-scenario probabilities by asset (rows are joint-scenarios, columns are assets)
 #' @param  p             a vector of probabilities associated with each scenario in matrix X
 #' @param  Options       a list of options....TBD

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/RobustBayesianAllocation.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/RobustBayesianAllocation.R	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/RobustBayesianAllocation.R	2012-07-11 17:56:29 UTC (rev 2145)
@@ -185,7 +185,7 @@
 #' @return cov_post             a covariance matrix the confidence weighted posterior covariance matrix of asset returns blended from the prior and sample covariance matrix
 #' @return time_post            a numeric
 #' @return nu_pst               a numeric
-#' \deqn { T_{1}  \equiv T_{0} + T
+#' \deqn{ T_{1}  \equiv T_{0} + T
 #' \\ \mu_{1}  \equiv \frac{1}{ T_{1} }  \big( T_{0}   \mu_{0}  + T \hat{ \mu } \big)  
 #' \\ \nu_{1}  \equiv \nu_{0} + T
 #' \\ \Sigma_{1}  \equiv  \big(  \nu_{0} \Sigma_{0}  + T \hat{ \Sigma } +  \frac{ \big(\mu_{0}  - \hat{\mu} \big) \big(\mu_{0}  - \hat{\mu} \big)' }{ \big( \frac{1}{T} +  \frac{1}{T_{0} }  \big) }

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/logToArithmeticCovariance.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/logToArithmeticCovariance.R	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/logToArithmeticCovariance.R	2012-07-11 17:56:29 UTC (rev 2145)
@@ -6,7 +6,7 @@
 #' @return                        a list containing two elements:
 #' @return  arithmeticMean          a numeric containing the mean arithmetic returns
 #' @return  arithmeticCovariance    a variance-covariance matrix in simple arithmetic return terms
-#' \deqn { M_{ \tau }^{i}  =  e^{  \mu ^{\tau} _{i} +  \frac{1}{2} \Sigma^{ii} _{\tau} },
+#' \deqn{ M_{ \tau }^{i}  =  e^{  \mu ^{\tau} _{i} +  \frac{1}{2} \Sigma^{ii} _{\tau} },
 #' \\  S^{ij} = e^{  \mu ^{\tau} _{i} + \mu ^{\tau} _{j} + \frac{1}{2} \big(\Sigma^{ii} _{\tau} + \Sigma^{jj} _{\tau}\big)  }  \big(e^{\Sigma^{ij} _{\tau}} - 1\big) }
 #' @author Ram Ahluwalia \email{ram@@wingedfootcapital.com}
 #' @export

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Central2Raw.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Central2Raw.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Central2Raw.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -16,14 +16,18 @@
   start with the first non-central moment and apply
   recursively an identity (formula 20)
 }
+\details{
+%  \deqn{ \tilde{ \mu }^{ \big(1\big) }_{X} \equiv \mu^{\big(1\big)}_{X} 
+%\\ \tilde{ \mu }^{ \big(n\big) }_{X}
+%  \equiv \mu^{n}_{X} \sum_{k=0}^{n-1} \big(-1\big)^{n-k+1}
+%  \mu^{n-k}_{X} \tilde{ \mu }^{\big(k\big)}_{X} }
+}
 \author{
-  Ram Ahluwalia \email{rahluwalia at gmail.com} \deqn{ \tilde{
-  \mu }^{ \big(1\big) }_{X} \equiv \mu ^{\big(1\big)}_{X}
-  \\ \tilde{ \mu }^{ \big(n\big) }_{X} \equiv \mu ^{n}_{X}
-  \sum_{k=0}^{n-1} \big(-1\big)^{n-k+1} \mu ^{n-k}_{X}
-  \tilde{ \mu }^{\big(k\big)}_{X} } A. Meucci - "Exercises
-  in Advanced Risk and Portfolio Management". See page 10.
-  Symmys site containing original MATLAB source code
-  \url{http://www.symmys.com}
+  Ram Ahluwalia \email{rahluwalia at gmail.com}
 }
+\references{
+  A. Meucci - "Exercises in Advanced Risk and Portfolio
+  Management". See page 10. Symmys site containing original
+  MATLAB source code \url{http://www.symmys.com}
+}
 

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/ComputeMVE.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/ComputeMVE.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/ComputeMVE.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -12,26 +12,32 @@
   list a list with MVE_Location a numeric with the location
   parameter of minimum volume ellipsoid MVE_Dispersion a
   numeric with the covariance matrix of the minimum volume
-  ellipsoid \deqn { w_{t} = \frac{1}{T} , t = 1,...,T \\ m
-  \equiv \frac{1}{ \sum_{s=1}^T w_{s} } \sum_{t=1}^T w_{t}
-  x_{t} \\ S \equiv \sum_{t=1}^T w_{t} \big(x_{t} - m\big)
+  ellipsoid
+}
+\description{
+  Function computes the minimum volume ellipsoid for a
+  given time series
+}
+\details{
+  via the expectations-minimization algorithm
+
+  \deqn{ w_{t} = \frac{1}{T} , t = 1,...,T \\ m \equiv
+  \frac{1}{ \sum_{s=1}^T w_{s} } \sum_{t=1}^T w_{t} x_{t}
+  \\ S \equiv \sum_{t=1}^T w_{t} \big(x_{t} - m\big)
   \big(x_{t} - m\big)' \\ Ma_{t}^{2} \equiv \big(x-m\big)'
   S^{-1} \big(x-m\big), t=1,...,T \\ w_{t} \mapsto w_{t}
   Ma_{t}^{2} \\ U = \big(x_{1}' - \hat{E}',...,x_{T}' -
   \hat{E}' \big) \\ \hat{Cov} \equiv \frac{1}{T} U'U }
+
+  The location and scatter parameters that define the
+  ellipsoid are multivariate high-breakdown estimators of
+  location and scatter
 }
-\description{
-  Function computes the minimum volume ellipsoid for a
-  given time series via the expectations-minimization
-  algorithm The location and scatter parameters that define
-  the ellipsoid are multivariate high-breakdown estimators
-  of location and scatter
-}
 \author{
   Ram Ahluwalia \email{ram at wingedfootcapital.com}
 }
 \references{
-  \url{http://www.symmys.com/sites/default/files/Risk%20and%20Asset%20Allocation%20-%20Springer%20Quantitative%20Finance%20-%20Estimation.pdf}
+  \url{http://www.symmys.com/sites/default/files/Risk\%20and\%20Asset\%20Allocation\%20-\%20Springer\%20Quantitative\%20Finance\%20-\%20Estimation.pdf}
   See Sec. 4.6.1 of "Risk and Asset Allocation" - Springer
   (2005), by A. Meucci for the theory and the routine
   implemented below See Meucci script for "ComputeMVE.m"

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/CondProbViews.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/CondProbViews.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/CondProbViews.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
 \name{CondProbViews}
 \alias{CondProbViews}
+\title{Input conditional views}
 \usage{
   CondProbViews(View, X)
 }
@@ -15,6 +16,17 @@
 
   g TBD
 }
+\description{
+  statement: View(k).Who (e.g. [1 3])= View(k).Equal (e.g.
+  {[2 3] [1 3 5]}) optional conditional statement:
+  View(k).Cond_Who (e.g. [2])= View(k).Cond_Equal (e.g.
+  {[1]}) amount of stress is quantified as Prob(statement)
+  <= View(k).v if View(k).sgn = 1; Prob(statement) >=
+  View(k).v if View(k).sgn = -1;
+}
+\details{
+  confidence in stress is quantified in View(k).c in (0,1)
+}
 \author{
   Ram Ahluwalia \email{ram at wingedfootcapital.com}
 }

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Cumul2Raw.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Cumul2Raw.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Cumul2Raw.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -8,17 +8,23 @@
   \item{ka}{cumulants of Y}
 }
 \value{
-  mu_ the raw non-central moments of Y \deqn {\tilde{ \mu }
-  ^{ \big(n\big) }_{Y} \equiv \kappa^{ \big(n\big) }_{Y} +
-  \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$ \kappa_{Y}^{
-  \big(k\big) } \tilde{ \mu } ^{n-k}_{Y} }
+  mu_ the raw non-central moments of Y
 }
 \description{
-  step 5 of the projection process: From the cumulants of Y
-  we compute the raw non-central moments of Y We do so
-  recursively by the identity in formula (24) which follows
-  from applying (21) and re-arranging terms
+  step 5 of the projection process:
 }
+\details{
+  From the cumulants of Y we compute the raw non-central
+  moments of Y
+
+  We do so recursively by the identity in formula (24)
+  which follows from applying (21) and re-arranging terms
+
+  \deqn{ \tilde{ \mu } ^{ \big(n\big) }_{Y} \\ \equiv
+  \kappa^{ \big(n\big) }_{Y} + \sum_{k=1}^{n-1} % ^{n-1}
+  C_{k-1} \\ \kappa_{Y}^{ \big(k\big) } \tilde{ \mu }
+  ^{n-k}_{Y} }
+}
 \author{
   Ram Ahluwalia \email{rahluwalia at gmail.com}
 }

Deleted: pkg/PerformanceAnalytics/sandbox/Meucci/man/EfficientFrontier.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/EfficientFrontier.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/EfficientFrontier.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,28 +0,0 @@
-\name{EfficientFrontier}
-\alias{EfficientFrontier}
-\usage{
-  EfficientFrontier(X, p, Options)
-}
-\arguments{
-  \item{X}{a matrix with the joint-scenario probabilities
-  by asset (rows are joint-scenarios, columns are assets)}
-
-  \item{p}{a vector of probabilities associated with each
-  scenario in matrix X}
-
-  \item{Options}{a list of options....TBD}
-}
-\value{
-  A list with NumPortf efficient portfolios whos returns
-  are equally spaced along the whole range of the efficient
-  frontier Exps the NumPortf x 1 vector of expected returns
-  for each asset Covs the NumPortf x N vector of security
-  volatilities along the efficient frontier w the NumPortf
-  x N matrix of compositions (security weights) for each
-  portfolio along the efficient frontier e the NumPortf x 1
-  matrix of expected returns for each portfolio along the
-  efficient frontier s the NumPortf x 1 matrix of standard
-  deviation of returns for each portfolio along the
-  efficient frontier
-}
-

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/GenerateLogNormalDistribution.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/GenerateLogNormalDistribution.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/GenerateLogNormalDistribution.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,6 +1,6 @@
 \name{GenerateLogNormalDistribution}
 \alias{GenerateLogNormalDistribution}
-\title{Generate arbitrary distribution of a shifted-lognormal invariant: X-t + a ~ LogN(m,s^2) (formula 14)}
+\title{Generate arbitrary distribution of a shifted-lognormal invariant}
 \usage{
   GenerateLogNormalDistribution(J, a, m, s)
 }
@@ -20,8 +20,7 @@
   parameters J, a, m, and s where X = a + exp( m + s * Z )
 }
 \description{
-  Generate arbitrary distribution of a shifted-lognormal
-  invariant: X-t + a ~ LogN(m,s^2) (formula 14)
+  %\deqn{X-t + a ~ LogN(m,s^2)} (formula 14)
 }
 \author{
   Ram Ahluwalia \email{rahluwalia at gmail.com}

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/PartialConfidencePosterior.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/PartialConfidencePosterior.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/PartialConfidencePosterior.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -42,13 +42,13 @@
 
   time_post a numeric
 
-  nu_pst a numeric \deqn { T_{1} \equiv T_{0} + T \\
-  \mu_{1} \equiv \frac{1}{ T_{1} } \big( T_{0} \mu_{0} + T
-  \hat{ \mu } \big) \\ \nu_{1} \equiv \nu_{0} + T \\
-  \Sigma_{1} \equiv \big( \nu_{0} \Sigma_{0} + T \hat{
-  \Sigma } + \frac{ \big(\mu_{0} - \hat{\mu} \big)
-  \big(\mu_{0} - \hat{\mu} \big)' }{ \big( \frac{1}{T} +
-  \frac{1}{T_{0} } \big) }
+  nu_pst a numeric \deqn{ T_{1} \equiv T_{0} + T \\ \mu_{1}
+  \equiv \frac{1}{ T_{1} } \big( T_{0} \mu_{0} + T \hat{
+  \mu } \big) \\ \nu_{1} \equiv \nu_{0} + T \\ \Sigma_{1}
+  \equiv \big( \nu_{0} \Sigma_{0} + T \hat{ \Sigma } +
+  \frac{ \big(\mu_{0} - \hat{\mu} \big) \big(\mu_{0} -
+  \hat{\mu} \big)' }{ \big( \frac{1}{T} + \frac{1}{T_{0} }
+  \big) }
 }
 \description{
   Constructs the partial confidence posterior based on

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/PlotDistributions.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/PlotDistributions.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/PlotDistributions.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
 \name{PlotDistributions}
 \alias{PlotDistributions}
+\title{plot dists}
 \usage{
   PlotDistributions(X, p, Mu, Sigma, p_, Mu_, Sigma_)
 }
@@ -18,6 +19,9 @@
 
   \item{Sigma_}{}
 }
+\description{
+  plot dists
+}
 \author{
   Ram Ahluwalia \email{ram at wingedfootcapital.com}
 }

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Prior2Posterior.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Prior2Posterior.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Prior2Posterior.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -25,8 +25,8 @@
 }
 \value{
   a list with M_ a numeric vector with the full-confidence
-  posterior distribution of Mu S_ a covariance matrix with
-  the full-confidence posterior distribution of Sigma
+  posterior distribution of \Mu S_ a covariance matrix with
+  the full-confidence posterior distribution of \Sigma
 }
 \description{
   Calculate the full-confidence posterior distributions of
@@ -37,12 +37,12 @@
 }
 \references{
   \url{http://www.symmys.com}
-  \url{http://ssrn.com/abstract=1213325} \deqn { \tilde{
-  \mu } \equiv \mu + \Sigma Q' {\big(Q \Sigma Q'
-  \big)}^{-1} \big( \tilde{\mu}_{Q} - Q \mu \big), \\
-  \tilde{ \Sigma } \equiv \Sigma + \Sigma G' \big({\big(G
-  \Sigma G' \big)}^{-1} \tilde{ \Sigma }_G {\big(G \Sigma
-  G' \big)}^{-1} - {\big(G \Sigma G' \big)}^{-1} \big) G
+  \url{http://ssrn.com/abstract=1213325} \deqn{ \tilde{ \mu
+  } \equiv \mu + \Sigma Q' {\big(Q \Sigma Q' \big)}^{-1}
+  \big( \tilde{\mu}_{Q} - Q \mu \big), \\ \tilde{ \Sigma }
+  \equiv \Sigma + \Sigma G' \big({\big(G \Sigma G'
+  \big)}^{-1} \tilde{ \Sigma }_G {\big(G \Sigma G'
+  \big)}^{-1} - {\big(G \Sigma G' \big)}^{-1} \big) G
   \Sigma } A. Meucci - "Fully Flexible Views: Theory and
   Practice". See formula (21) and (22) on page 7 See Meucci
   script Prior2Posterior.m attached to Entropy Pooling

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Central.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Central.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Central.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -9,17 +9,21 @@
   Y-t}
 }
 \value{
-  mu (multi-period) central moment of Y-t \deqn {\tilde{
-  \mu } ^ {\big(n\big)} _{X} \equiv E \big\{ X^{n} \big\},
-  \\ \mu ^{ \big(n\big) }_{X} \equiv \sum_0^{n-1}
-  \big(-1\big)^{n-k} \mu ^{n-k}_{X} \tilde{ \mu }^{k}_{X} +
-  \tilde{ \mu }_{X}^{n} }
+  mu (multi-period) central moment of Y-t
 }
 \description{
-  step 6 of projection process: compute multi-period
-  central moments. Note the first central moment defined as
-  expectation.
+  step 6 of projection process:
 }
+\details{
+  compute multi-period central moments.
+
+  Note the first central moment defined as expectation.
+
+%  \deqn{\tilde{ \mu } ^ {\big(n\big)} _{X} \equiv E
+%  \big\{ X^{n} \big\}, \\ \mu^{ \big(n\big) }_{X} \equiv
+%  \sum_0^{n-1} \big{ -1 \big}^{n-k} \mu^{n-k}_{X} \tilde{
+%  \mu }^{k}_{X} + \tilde{ \mu }_{X}^{n} }
+}
 \author{
   Ram Ahluwalia \email{rahluwalia at gmail.com}
 }

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Cumul.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Cumul.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Cumul.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -8,19 +8,23 @@
   \item{mu_}{non-central moments of the invariant X-t}
 }
 \value{
-  ka cumulants of X-t \deqn { \kappa^{ \big(n\big) }_{X}
-  \equiv \tilde{ \mu } ^{ \big(n\big) }_{X} -
-  \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$ \kappa_{X}^{
-  \big(k\big) } \tilde{ \mu } ^{n-k}_{X} }
+  ka cumulants of X-t
 }
 \description{
   Step 3 of the projection process: From the non-central
-  moments of X-t, we compute the cumulants. This process
-  follows from the Taylor approximations for any small z
-  and ln(1+x)~x for any small x, and from the definition of
-  the first cumulant in (17). The we apply recursively the
-  identity in formula (21). See Kendall and Stuart (1969)
+  moments of X-t, we compute the cumulants.
 }
+\details{
+  This process follows from the Taylor approximations for
+  any small z and ln(1+x)~x for any small x, and from the
+  definition of the first cumulant in (17). The we apply
+  recursively the identity in formula (21). See Kendall and
+  Stuart (1969)
+
+%  \deqn{ \kappa^{ \big(n\big) }_{X} \equiv \tilde{ \mu } ^{
+%  \big(n\big) }_{X} - \sum_{k=1}^{n-1} $^{n-1} C_{k-1} %$
+%  \kappa_{X}^{ \big(k\big) } \tilde{ \mu } ^{n-k}_{X} }
+}
 \author{
   Ram Ahluwalia \email{rahluwalia at gmail.com}
 }

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/StackedBarChart.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/StackedBarChart.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/StackedBarChart.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
 \name{StackedBarChart}
 \alias{StackedBarChart}
+\title{Generate a Stacked Bar Chart based on the frontier weights matrix}
 \usage{
   StackedBarChart(weightsMatrix)
 }
@@ -9,4 +10,8 @@
 
   \item{a}{string indicating the title of the chart}
 }
+\description{
+  Generate a Stacked Bar Chart based on the frontier
+  weights matrix
+}
 

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Tweak.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Tweak.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Tweak.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
 \name{Tweak}
 \alias{Tweak}
+\title{tweak a matrix}
 \usage{
   Tweak(A, b, g)
 }
@@ -15,6 +16,9 @@
 \value{
   db
 }
+\description{
+  tweak a matrix
+}
 \author{
   Ram Ahluwalia \email{ram at wingedfootcapital.com}
 }

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/ViewRanking.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/ViewRanking.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/ViewRanking.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
 \name{ViewRanking}
 \alias{ViewRanking}
+\title{view the rankings}
 \usage{
   ViewRanking(X, p, Lower, Upper)
 }
@@ -10,4 +11,7 @@
   \item{Upper}{a vector of indexes indicating which column
   is lower than the corresponding column number in Upper}
 }
+\description{
+  view the rankings
+}
 

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/linreturn.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/linreturn.Rd	2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/linreturn.Rd	2012-07-11 17:56:29 UTC (rev 2145)
@@ -17,7 +17,7 @@
   returns
 
   arithmeticCovariance a variance-covariance matrix in
-  simple arithmetic return terms \deqn { M_{ \tau }^{i} =
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/returnanalytics -r 2145


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