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# file : fitPareto.r
# author: Mark van der Loo (mark.vanderloo@gmail.com)
#
# Determine parameters ym (scale) and alpha (shape)
# of a pareto distributed variable Y, by fitting (part of)
# the log(cdf) to an observed log(cdf).
#
# INPUT
# y : vector of observed values
# p : vector of observed quantiles (y_i estimates the p_i'th quantile)
#
# OUTPUT (list)
# ym : estimate of scale parameter
# alpha : estimate of shape parameter
# R2 : R-squared value of fit. (logarithmic)
#
# History
# 22.10.2009 version 1
#
fitPareto <- function(y,p)
{
if ( !is.vector(y) )
stop("First argument is not of type vector")
if ( sum(y<=0) > 0 )
stop("First argument contains nonpositive values")
if ( !is.vector(p))
stop("First argument is not of type vector")
if ( sum(p<=0) > 0 | sum(p>=1) >0 )
stop("Second argument contains values out of range (0,1)")
if (length(y) != length(p))
stop("First and second argument have different length");
N <- length(y);
lnY <- as.matrix(log(y),nrow=N)
p <- as.matrix(p,nrow=N)
A <- matrix(0,nrow=N,ncol=2)
A[,1] <- 1 + double(N);
A[,2] <- log(1-p);
param <- solve(t(A) %*% A)%*%t(A)%*%lnY
r2 <- 1 - var(exp(A%*%param) - y)/var(y);
return(list(ym=exp(param[1]), alpha=-1/param[2], R2=r2));
}
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