Lmoments (version 1.3-2)

data2normpoly: Estimation of normal-polynomial quantile mixture

Description

Estimates the parameters of normal-polynomial quantile mixture from data or from L-moments

Usage

data2normpoly4(data)
lmom2normpoly4(lmom)
data2normpoly6(data)
lmom2normpoly6(lmom)

Value

vector or matrix containing the four or six parameters of normal-polynomial quantile mixture

Arguments

data

matrix or data frame

lmom

vector or matrix of L-moments

Author

Juha Karvanen

References

Karvanen, J. 2006. Estimation of quantile mixtures via L-moments and trimmed L-moments, Computational Statistics & Data Analysis 51, (2), 947--959. https://users.jyu.fi/~jutakarv/papers/Karvanen_quantile_mixtures.pdf.

See Also

dnormpoly for L-moments, dnormpoly for the normal-polynomial quantile mixture and data2cauchypoly4 for the estimation of Cauchy-polynomial quantile mixture.

Examples

#Generates a sample 500 observations from the normal-polynomial quantile mixture, 
#calculates L-moments and their covariance matrix,
#estimates parameters via L-moments and 
#plots the true pdf and the estimated pdf together with the histogram of the data.
true_params <- lmom2normpoly4(c(0,1,0.2,0.05));
x <- rnormpoly(500,true_params);
lmoments <- Lmoments(x);
lmomcov <- Lmomcov(x);
estim_params <- lmom2normpoly4(lmoments);
hist(x,30,freq=FALSE);
plotpoints <- seq(min(x)-1,max(x)+1,by=0.01);
lines(plotpoints, dnormpoly(plotpoints,estim_params), col='red');
lines(plotpoints, dnormpoly(plotpoints,true_params), col='blue');