t1lmoments {Lmoments} | R Documentation |
Calculates sample trimmed L-moments with trimming parameter 1.
t1lmoments(data,rmax=4)
data |
matrix or data frame. |
rmax |
maximum order of trimmed L-moments. |
array of trimmed L-moments (trimming parameter = 1) up to order 4 containing a row for each variable in data.
Functions link{Lmoments}
and link{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. 2003. Trimmed L-moments, Computational Statistics & Data Analysis 43, 299–314.
Lmoments
for L-moments, and
dcauchypoly
and t1lmom2cauchypoly4
for the Cauchy-polynomial quantile mixture
#Generates 500 random variables from the Cauchy-polynomial quantile mixture, #calculates the trimmed L-moments, #estimates parameters via trimmed L-moments and #plots the true pdf and the estimated pdf together with the histogram of the data. true_params<-t1lmom2cauchypoly4(c(0,1,0.075,0.343)); x<-rcauchypoly(500,true_params); t1lmom<-t1lmoments(x); estim_params<-t1lmom2cauchypoly4(t1lmom); plotpoints<-seq(-10,10,by=0.01); histpoints<-c(seq(min(x)-1,-20,length.out=50),seq(-10,10,by=0.5),seq(20,max(x)+1,length.out=50)); hist(x,breaks=histpoints,freq=FALSE,xlim=c(-10,10)); lines(plotpoints,dcauchypoly(plotpoints,estim_params),col='red'); lines(plotpoints,dcauchypoly(plotpoints,true_params),col='blue');