Nothing
rgeneral.test <- function(m, n=2, k=n, segments=NULL, p=0.5, x.u=1 )
{
###
### This function generates m random general portfolios with n investments each
### Each portfolio has k positions that can be positive or negative.
### The probability that a given non-zero position is
### positive is p. The maximum absolute exposure is x.u which has 1 as the default
###
### Arguments
### m = a positive integer value for the number of portfolios to be generated
### n = a positive integer value for the number of investments in a portfolio
### p = a positive numeric value for the probability that an investment has positive weight
### x.u = a positive numeric value for the maximum absolute exposure to an investment
###
if ( missing( m ) )
stop( "Argument 'm' is missing" )
if ( m <= 0 ) {
stop( "Argument 'm' is not positive" )
}
###
### private function
###
by.case <- function( case, number, size, theSegments, probability, limit )
{
return( random.general.test( n=number, k=size, segments=theSegments,
p=probability, x.u=limit ) )
}
results <- lapply( 1:m, by.case, n, k, segments, p, x.u )
###
### separate the investment weights and iterations into a matrix and vector
###
xmatrix <- matrix( 0, nrow=m, ncol=n )
iters <- rep( 0, m )
for ( case in 1:m ) {
thisResult <- results[[case]]
iters[case] <- thisResult$iter
xmatrix[case,] <- thisResult$x
}
###
### create a new result list
###
result <- list( xmatrix=xmatrix, iters=iters )
return( result )
}
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