Lmoments {Lmoments} | R Documentation |
Calculates sample L-moments, L-coefficients and covariance matrix of L-moments.
Lmoments(data,rmax=4,na.rm=FALSE,returnobject=FALSE,trim=c(0,0)) Lcoefs(data,rmax=4,na.rm=FALSE,trim=c(0,0)) Lmomcov(data,rmax=4,na.rm=FALSE) Lmoments_calc(data,rmax=4) Lmomcov_calc(data,rmax=4)
data |
matrix or data frame. |
rmax |
maximum order of L-moments. |
na.rm |
a logical value indicating whether 'NA' values should be removed before the computation proceeds. |
returnobject |
a logical value indicating whether a list object should be returned instead of an array of L-moments. |
trim |
c(0,0) for ordinary L-moments and c(1,1) for trimmed (t=1) L-moments |
Lmoments |
returns an array of L-moments containing a row for each variable in data, or if returnobject=TRUE,
a list containing
|
Lcoefs |
returns an array of L-coefficients (mean, L-scale, L-skewness, L-kurtosis, ...) containing a row for each variable in data. |
Lmomcov |
returns the covariance matrix of L-moments or a list of covariance matrices if the input has multiple columns. |
Lmoments_calc |
is internal function. |
Lmomcov_calc |
is internal function. |
Functions Lmoments
and Lcoefs
calculate trimmed L-moments if you specify trim=c(1,1)
.
Juha Karvanen <juha.karvanen@ktl.fi>
Karvanen, J. 2005. Estimation of quantile mixtures via L-moments and trimmed L-moments, Computational Statistics & Data Analysis, in press, http://www.bsp.brain.riken.jp/publications/2005/karvanen_quantile_mixtures.pdf.
Elamir, E. A., Seheult, A. H. 2004. Exact variance structure of sample L-moments, Journal of Statistical Planning and Inference 124 (2) 337–359.
Hosking, J. 1990. L-moments: Analysis and estimation distributions using linear combinations of order statistics, Journal of Royal Statistical Society B 52, 105–124.
t1lmoments
for trimmed L-moments,
dnormpoly
, lmom2normpoly4
and covnormpoly4
for the normal-polynomial quantile mixture
and package lmomco for additional L-moment functions
#Generates a sample 500 observations from the normal-polynomial quantile mixture, #calculates the 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');