R: Estimation of normal-polynomial quantile mixture

data2normpoly {Lmoments} | R Documentation

## 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)

### Arguments

`data` | matrix or data frame
`lmom` | vector or matrix of L-moments

### Value

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

### Author(s)

Juha Karvanen juha.karvanen@iki.fi

### References

Karvanen, J. 2006. Estimation of quantile mixtures via L-moments and trimmed L-moments, Computational Statistics & Data Analysis 51, (2), 947–959. http://www.bsp.brain.riken.jp/publications/2006/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');

[Package Lmoments version 1.2-3 Index]