merge and comment out url in KellyRatio.R

Merge branch 'master' of github.com:braverock/PerformanceAnalytics

# Conflicts:
#	R/KellyRatio.R

.Rbuildignore

@@ -9,4 +9,5 @@ codeblock.txt
 ^\.travis.yml
 cran-comments.md
 ^\.github$
-PerformanceAnalytics-Ex.Rout.save
+PerformanceAnalytics-Ex.Rout.save
+textplotPresentation-CRUG-2011.Rnw

DESCRIPTION

@@ -19,8 +19,8 @@ Authors@R: c(
   , person(given=c("Justin", "M."),family="Shea",role="ctb")
   , person(given="Dhairya",family="Jain",role="ctb")
   )
-Version: 2.0.8
-Date: 2024-12-04
+Version: 2.0.8-1
+Date: 2024-12-09
 Description: Collection of econometric functions for performance and risk 
     analysis. In addition to standard risk and performance metrics, this 
     package aims to aid practitioners and researchers in utilizing the latest
@@ -62,5 +62,5 @@ License: GPL-2 | GPL-3
 Encoding: UTF-8
 LazyData: true
 URL: https://github.com/braverock/PerformanceAnalytics
-Copyright: (c) 2004-2022
+Copyright: (c) 2004-2024
 RoxygenNote: 7.3.2

R/CAPM.alpha.R

@@ -10,24 +10,24 @@
 #' literature, it is an example of a simple single factor model, 
 #' comparing an asset to any arbitrary benchmark.
 #'  
-#' @aliases CAPM.alpha
+#' @aliases CAPM.alpha SFM.alpha
 #' @param Ra an xts, vector, matrix, data frame, timeSeries or zoo object of
 #' asset returns
 #' @param Rb return vector of the benchmark asset
 #' @param Rf risk free rate, in same period as your returns
 #' @param \dots Other parameters like max.it or bb specific to lmrobdetMM regression.
-#' @param digits (Optional): Number of digits to round the results to. Defaults to 3.
-#' @param benchmarkCols (Optional): Boolean to show the benchmarks as columns. Defaults to TRUE.
-#' @param method (Optional): string representing linear regression model, "LS" for Least Squares
-#'                    and "Robust" for robust. Defaults to "LS      
-#' @param family (Optional): 
+#' @param digits Number of digits to round the results to. Defaults to 3.
+#' @param benchmarkCols Boolean to show the benchmarks as columns. Defaults to TRUE.
+#' @param method string representing linear regression model, "LS" for Least Squares
+#'                    and "Robust" for robust. Defaults to "LS"      
+#' @param family 
 #'         If method == "Robust": 
 #'           This is a string specifying the name of the family of loss function
 #'           to be used (current valid options are "bisquare", "opt" and "mopt").
 #'           Incomplete entries will be matched to the current valid options. 
 #'           Defaults to "mopt".
 #'         Else: the parameter is ignored
-#' @param warning (Optional): Boolean to show warnings or not. Defaults to TRUE.
+#' @param warning Boolean to show warnings or not. Defaults to TRUE.
 #' 
 #' @author Dhairya Jain, Peter Carl
 #' @seealso \code{\link{CAPM.beta}} \code{\link{CAPM.utils}}
@@ -42,15 +42,16 @@
 #'     data(managers)
 #'     SFM.alpha(managers[, "HAM1"], managers[, "SP500 TR"], Rf = managers[, "US 3m TR"])
 #'     SFM.alpha(managers[,1:3], managers[,8:10], Rf=.035/12) 
-#'     SFM.alpha(managers[,1], managers[,8:10], Rf=.035/12, benchmarkCols=FALSE) 
+#'     # SFM.alpha(managers[,1], managers[,8:10], Rf=.035/12, benchmarkCols=FALSE) # other variations
+#' if(requireNamespace("RobStatTM", quietly = TRUE)) { # CRAN requires conditional execution
+#'    alphas <- SFM.alpha(managers[,1:6], 
+#' 		                  	managers[,8:10], 
+#' 			                  Rf=.035/12, method="Robust", 
+#' 			                  family="opt", bb=0.25, max.it=200, digits=4)
+#' 	  alphas["HAM1", ]
+#' 	  alphas[, "Alpha : SP500 TR"]
+#' } # CRAN can have issues with RobStatTM 
 #'
-#'     alphas <- SFM.alpha(managers[,1:6], 
-#' 			managers[,8:10], 
-#' 			Rf=.035/12, method="Robust", 
-#' 			family="opt", bb=0.25, max.it=200, digits=4)
-#' 	     alphas["HAM1", ]
-#' 	     alphas[, "Alpha : SP500 TR"]
-#' 
 #' @rdname SFM.alpha
 #' @export SFM.alpha CAPM.alpha
 SFM.alpha <- CAPM.alpha <- function (Ra, Rb, Rf = 0,  ..., digits=3, benchmarkCols = T, method="LS", family="mopt", warning=T){

R/CAPM.beta.R

@@ -62,49 +62,54 @@
 #' @examples
 #' 
 #' data(managers)
-#'     SFM.beta(managers[, "HAM1"], managers[, "SP500 TR"], Rf = managers[, "US 3m TR"])
-#'     SFM.beta(managers[,1:3], managers[,8:10], Rf=.035/12) 
-#'     SFM.beta(managers[,1], managers[,8:10], Rf=.035/12, benchmarkCols=FALSE) 
+#' 
+#' SFM.beta(managers[, "HAM1"], managers[, "SP500 TR"], Rf = managers[, "US 3m TR"])
+#' SFM.beta(managers[,1:3], managers[,8:10], Rf=.035/12) 
+#' SFM.beta(managers[,1], managers[,8:10], Rf=.035/12, benchmarkCols=FALSE) 
 #'
-#'     betas <- SFM.beta(managers[,1:6], 
-#' 			managers[,8:10], 
-#' 			Rf=.035/12, method="Robust", 
-#' 			family="opt", bb=0.25, max.it=200, digits=4)
-#' 	     betas["HAM1", ]
-#' 	     betas[, "Beta : SP500 TR"]
+#' SFM.beta.bull(managers[, "HAM2"], 
+#' 			         managers[, "SP500 TR"], 
+#' 			         Rf = managers[, "US 3m TR"])
+#' 			         
+#' SFM.beta.bear(managers[, "HAM2"], 
+#' 			         managers[, "SP500 TR"], 
+#' 			         Rf = managers[, "US 3m TR"])
+#' 			
+#' TimingRatio(managers[, "HAM2"], 
+#' 			       managers[, "SP500 TR"], 
+#' 			       Rf = managers[, "US 3m TR"])
+#' 			
+#' if(requireNamespace("RobStatTM", quietly = TRUE)) { # CRAN requires conditional execution
+#'   betas <- SFM.beta(managers[,1:6], 
+#' 			               managers[,8:10], 
+#' 			               Rf=.035/12, method="Robust", 
+#' 			               family="opt", bb=0.25, max.it=200, digits=4)
+#' 	 betas["HAM1", ]
+#' 	 betas[, "Beta : SP500 TR"]
 #' 	     
-#' 	   SFM.beta.bull(managers[, "HAM2"], 
-#' 			managers[, "SP500 TR"], 
-#' 			Rf = managers[, "US 3m TR"])
-#'     SFM.beta.bull(managers[, "HAM2"], 
-#' 			managers[, "SP500 TR"], 
-#' 			Rf = managers[, "US 3m TR"],
-#' 			method="Robust")
+#'   SFM.beta.bull(managers[, "HAM2"], 
+#' 	               managers[, "SP500 TR"], 
+#' 			           Rf = managers[, "US 3m TR"],
+#' 			           method="Robust")
 #' 			
-#' 	   SFM.beta.bear(managers[, "HAM2"], 
-#' 			managers[, "SP500 TR"], 
-#' 			Rf = managers[, "US 3m TR"])
-#'     SFM.beta.bear(managers[, "HAM2"], 
-#' 			managers[, "SP500 TR"], 
-#' 			Rf = managers[, "US 3m TR"],
-#' 			method="Robust")
+#'   SFM.beta.bear(managers[, "HAM2"], 
+#' 			           managers[, "SP500 TR"], 
+#' 			           Rf = managers[, "US 3m TR"],
+#' 			           method="Robust")
+#' 			           
+#' 	 TimingRatio(managers[, "HAM2"], 
+#' 	         		 managers[, "SP500 TR"], 
+#' 			         Rf = managers[, "US 3m TR"],
+#' 			         method="Robust", family="mopt")
 #' 			
-#'     TimingRatio(managers[, "HAM2"], 
-#' 			managers[, "SP500 TR"], 
-#' 			Rf = managers[, "US 3m TR"])
-#' 	   TimingRatio(managers[, "HAM2"], 
-#' 			managers[, "SP500 TR"], 
-#' 			Rf = managers[, "US 3m TR"],
-#' 			method="Robust", family="mopt")
-#' 
-#'     chart.Regression(managers[, "HAM2"], 
-#' 			managers[, "SP500 TR"], 
-#' 			Rf = managers[, "US 3m TR"], 
-#' 			fit="conditional", 
-#' 			main="Conditional Beta")
-#'   		
-#'   		
-
+#' } # CRAN can have issues with RobStatTM
+#' 			
+#' chart.Regression(managers[, "HAM2"], 
+#' 			            managers[, "SP500 TR"], 
+#' 			            Rf = managers[, "US 3m TR"], 
+#' 			            fit="conditional", 
+#' 			            main="Conditional Beta")
+#'
 #' @rdname SFM.beta
 #' @export SFM.beta CAPM.beta
 SFM.beta <- CAPM.beta <- function (Ra, Rb, Rf = 0, ..., digits=3, benchmarkCols=T, method="LS", family="mopt", warning=T)

R/ES.R

@@ -213,10 +213,7 @@
 #' expected shortfall. Mathematical Finance, 2002, vol. 14, 74-86.
 ###keywords ts multivariate distribution models
 #' @examples
-#' 
-#' if(!( Sys.info()[['sysname']]=="Windows") ){
-#' # if on Windows, cut and paste this example
-#' 
+#' \donttest{ 
 #'     data(edhec)
 #' 
 #'     # first do normal ES calc
@@ -232,12 +229,16 @@
 #'     ES(edhec, p=.99)
 #'     # or the equivalent alpha=.01
 #'     ES(edhec, p=.01)
-#' 
-#'     # now with outliers squished
-#'     ES(edhec, clean="boudt")
-#' 
-#'     # add Component ES for the equal weighted portfolio
-#'     ES(edhec, clean="boudt", portfolio_method="component")
+#'     
+#'     # CRAN (questionably(ahem) requires these methods to not run if you don't have Suggests loaded)
+#'     if(requireNamespace("robustbase", quietly = TRUE)){
+#        now with outliers squished
+#'       ES(edhec, clean="boudt")
+#' 
+#'       # add Component ES for the equal weighted portfolio
+#'       ES(edhec, clean="boudt", portfolio_method="component")
+#'     } # end CRAN workaround
+#'     
 #' 
 #' } # end CRAN Windows check
 #'     

R/KellyRatio.R

@@ -25,8 +25,9 @@
 #' @author Brian G. Peterson
 #' @references Thorp, Edward O. (1997; revised 1998). The Kelly Criterion in
 #' Blackjack, Sports Betting, and the Stock Market. #https://archive.ph/h1LuS
-#' \url{https://en.wikipedia.org/wiki/Kelly_criterion}
-###keywords ts multivariate distribution models
+#' no longer online, but can be found at archive.ph /h1LuS \cr
+#
+# ## keywords ts multivariate distribution models
 #' @examples
 #' 
 #'     data(managers)

R/Omega.R

@@ -65,9 +65,12 @@
 #' 
 #'     data(edhec)
 #'     Omega(edhec)
-#'     Omega(edhec[,13],method="interp",output="point")
-#'     Omega(edhec[,13],method="interp",output="full")
-#' 
+#'     
+#'     # CRAN (questionably(ahem) requires these methods to not run if you don't have Suggests loaded)
+#'     if(requireNamespace("Hmisc", quietly = TRUE)){
+#'       Omega(edhec[,13],method="interp",output="point")
+#'       Omega(edhec[,13],method="interp",output="full")
+#'     } # end  spurious CRAN check
 #' @export
 Omega <-
 function(R, L = 0, method = c("simple", "interp", "binomial", "blackscholes"), 

R/Return.calculate.R

@@ -48,7 +48,7 @@
 ###keywords ts multivariate distribution models
 #' @examples
 #' 
-#'   \dontrun{
+#'   \dontrun{ # no internet access on CRAN tests
 #'     require(quantmod)
 #'     prices = Cl(getSymbols("IBM", from = "1999-01-01", to = "2007-01-01"))
 #'   }

R/Return.locScaleRob.R

@@ -24,8 +24,9 @@
 #'                  "ED", "FIA", "GM", "LS", "MA",
 #'                  "RV", "SS", "FOF")
 #' # Cleaning the returns time series for manager data
-#' outRob <- Return.locScaleRob(edhec$CA)
-#'
+#' if(requireNamespace("RobStatTM", quietly = TRUE)) { # CRAN requires conditional execution
+#'   outRob <- Return.locScaleRob(edhec$CA)
+#' }
 # Implementation of the robust filter for the IF TS
 Return.locScaleRob <- function(R, alpha.robust=0.05, normal.efficiency=0.99, ...){
 

R/SFM.coefficients.R

@@ -50,16 +50,15 @@
 #' performance measurement and attribution}. Wiley. 2004. \cr
 ###keywords ts multivariate distribution models
 #' @examples
-#' 
-#' data(managers)
-#'      SFM.coefficients(managers[,1], managers[,8]) 
-#'      SFM.coefficients(managers[,1:6], managers[,8:9], Rf = managers[,10])
-#' 			SFM.coefficients(managers[,1:6], managers[,8:9], 
+#' if(requireNamespace("RobStatTM", quietly = TRUE)) { # CRAN requires conditional execution
+#'   data(managers)
+#'   SFM.coefficients(managers[,1], managers[,8]) 
+#'   SFM.coefficients(managers[,1:6], managers[,8:9], Rf = managers[,10])
+#' 	 SFM.coefficients(managers[,1:6], managers[,8:9], 
 #' 			     Rf=.035/12, method="Robust", 
 #' 			     family="mopt", bb=0.25, 
 #' 			     max.it=200)
-#' 			     
-#'   	  
+#' } # CRAN requires conditional execution
 #' @rdname SFM.coefficients
 #' @export SFM.coefficients
 SFM.coefficients <- function(Ra, Rb, Rf=0, subset=TRUE, ..., method="Robust", 
@@ -105,7 +104,7 @@ SFM.coefficients <- function(Ra, Rb, Rf=0, subset=TRUE, ..., method="Robust",
   Rb.colnames <- colnames(Rb)
 
   # ret.Model == TRUE means internal usage. Hence, if not internal usage
-  if (Model==F){
+  if (Model==FALSE){
     if (warning && method=="Both"){
       warning("Using 'Both' while using SFM.Coefficients will lead to ill-formatted output");
     }
@@ -195,15 +194,7 @@ SFM.coefficients <- function(Ra, Rb, Rf=0, subset=TRUE, ..., method="Robust",
 
     # FUNCTION:
 
-    if (!requireNamespace("RobStatTM", quietly=TRUE)){
-      c = readline(prompt = "You need to install package RobStatTM to use this function. Do you want to install it? (y|N): "); 
-      if(c=="y" || c=="Y"){
-        utils::install.packages("RobStatTM")
-      }
-      else{
-        stop("Aborted")
-      }
-    }
+
     # subset is assumed to be a logical vector
     if(missing(subset))
       subset <-TRUE
@@ -228,6 +219,8 @@ SFM.coefficients <- function(Ra, Rb, Rf=0, subset=TRUE, ..., method="Robust",
                           model= model.lm))
            },
            Robust = {
+             stopifnot("package:RobStatTM" %in% search() || requireNamespace("RobStatTM", quietly = TRUE))    
+
              model.rob.lm = RobStatTM::lmrobdetMM(Alpha ~ Beta, data=merged, 
                                        subset=subset, 
                                        control = RobStatTM::lmrobdet.control(family=family, ...))
@@ -236,6 +229,8 @@ SFM.coefficients <- function(Ra, Rb, Rf=0, subset=TRUE, ..., method="Robust",
                           model= model.rob.lm))
            },
            Both = {
+             stopifnot("package:RobStatTM" %in% search() || requireNamespace("RobStatTM", quietly = TRUE))    
+
              model.rob.lm = RobStatTM::lmrobdetMM(Alpha ~ Beta, data=merged,
                                        subset=subset,
                                        control = RobStatTM::lmrobdet.control(family=family))

R/SFM.fit.models.R

@@ -20,7 +20,7 @@
 #' @param plots Boolean to output plots after the function. Defaults to TRUE
 #' @author Dhairya Jain
 #' @examples 
-#' 
+#' \dontrun{
 #' # First we load the data
 #'     data(managers)
 #'     mgrs <- managers["2002/"]  # So that all have managers have complete history
@@ -42,7 +42,7 @@
 #' 		 
 #' 		 SFM.fit.models(mgrs$HAM2, mgrs$SP500, Rf = mgrs$RF, family = "opt", 
 #' 		                plots=FALSE)
-#'
+#' }
 #' @rdname SFM.fit.models
 #' @export SFM.fit.models
 SFM.fit.models <- function(Ra, Rb, Rf=0, family = "mopt", 

R/StdDev.R

@@ -62,10 +62,7 @@
 #' @seealso \code{\link{Return.clean}} \code{sd}
 ###keywords ts multivariate distribution models
 #' @examples
-#' 
-#' if(!( Sys.info()[['sysname']]=="Windows") ){
-#' # if on Windows, cut and paste this example
-#' 
+#' \donttest{
 #'     data(edhec)
 #' 
 #'     # first do normal StdDev calc
@@ -79,7 +76,7 @@
 #'     # add Component StdDev for the equal weighted portfolio
 #'     StdDev(edhec, clean="boudt", portfolio_method="component")
 #' 
-#' } # end CRAN Windows check
+#' } # end CRAN check
 #' 
 #' @export
 StdDev <- function (R , ..., clean=c("none","boudt","geltner", "locScaleRob"),  portfolio_method=c("single","component"), 

R/VaR.R

@@ -297,10 +297,7 @@
 #'      
 ###keywords ts multivariate distribution models
 #' @examples
-#' 
-#' if(!( Sys.info()[['sysname']]=="Windows") ){
-#' # if on Windows, cut and paste this example
-#' 
+#' \donttest{
 #'     data(edhec)
 #' 
 #'     # first do normal VaR calc
@@ -323,7 +320,7 @@
 #'     # add Component VaR for the equal weighted portfolio
 #'     VaR(edhec, clean="boudt", portfolio_method="component")
 #' 
-#' } # end Windows check
+#' } # end CRAN check
 #' 
 #' @export
 VaR <-