[Returnanalytics-commits] r2188 - pkg/PerformanceAnalytics/sandbox/Meucci/demo

[noreply at r-forge.r-project.org]

Author: mkshah
Date: 2012-07-23 01:22:37 +0200 (Mon, 23 Jul 2012)
New Revision: 2188

Modified:
   pkg/PerformanceAnalytics/sandbox/Meucci/demo/InvariantProjection.R
Log:
Removing Roxygen like commenting

Modified: pkg/PerformanceAnalytics/sandbox/Meucci/demo/InvariantProjection.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/demo/InvariantProjection.R	2012-07-21 16:23:23 UTC (rev 2187)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/demo/InvariantProjection.R	2012-07-22 23:22:37 UTC (rev 2188)
@@ -1,22 +1,22 @@
-#' Annualization and Projection algorithm for invariant
-#'
-#' Project summary statistics to arbitrary horizons under i.i.d. assumption
-#' SYMMYS - Last version of article and code available at http://symmys.com/node/136
-#' Project summary statistics to arbitrary horizons under i.i.d. assumption
-#' see Meucci, A. (2010) "Annualization and General Projection of Skewness, Kurtosis and All Summary Statistics"
-#' GARP Risk Professional, August, pp. 52-54
-#'
-#' @param    N    
-#' @param    K    
-#' @param    X    a numeric vector consisting of a generic (additive) invariant the 
-#'                  follows the general linear and square-root rules for projecting means and volatility
-#'
-#' @return   Ga   a numeric vector with the first 'N' order statistics projected to the horizon 'K'
-#' @export
-#' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
-#' @examples
-#'           X = GenerateLogNormalDistribution( J = 100000 , a = 01 , m = .2 , s = .4 ) # X = a + exp( m + s * Z ) # generate log-normal distribution
-#'           moments = ProjectInvariant( N = 6 , K = 251 , X )
+# Annualization and Projection algorithm for invariant
+#
+# Project summary statistics to arbitrary horizons under i.i.d. assumption
+# SYMMYS - Last version of article and code available at http://symmys.com/node/136
+# Project summary statistics to arbitrary horizons under i.i.d. assumption
+# see Meucci, A. (2010) "Annualization and General Projection of Skewness, Kurtosis and All Summary Statistics"
+# GARP Risk Professional, August, pp. 52-54
+#
+# @param    N    
+# @param    K    
+# @param    X    a numeric vector consisting of a generic (additive) invariant the 
+#                  follows the general linear and square-root rules for projecting means and volatility
+#
+# @return   Ga   a numeric vector with the first 'N' order statistics projected to the horizon 'K'
+# @export
+# @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
+# @examples
+#           X = GenerateLogNormalDistribution( J = 100000 , a = 01 , m = .2 , s = .4 ) # X = a + exp( m + s * Z ) # generate log-normal distribution
+#           moments = ProjectInvariant( N = 6 , K = 251 , X )
 
 N = 6   # a numeric with the number of the first N stadardized summary statistics to project
 K = 100 # a numeric with an arbitrary projection horizon