XploRe Help : estexp

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library:	stats
See also:	pdfexp cdfexp

Quantlet:		estexp
Description:		computes estimators of parameter (beta) of exponential distribution.

Reference(s):

K. Burnecki, A. Misiorek, R.Weron (2004) "Loss distibution", in “Statistical Tools for Finance and Insurance”, eds. P. Cizek, W. Härdle, R. Weron, Springer.

Usage:	`{db,de,vb,ve,w2b,w2e,a2b,a2e,beta,betamin} = estexp(analyzedsample,method,numberofiterations)`
Input:
	`analyzedsample`	n x 1 vector, sample for which exponential distribution parameters will be estimated.
	`method`	integer, estimation method selection flag (0 - all methods, other - ML).
	`numberofiterations`	integer, number of iterations for minimization procedures.
Output:
	`db`	scalar, Value of Kolmogorov statistic for ML parameters.
	`de`	scalar, Value of Kolmogorov statistic for A2 parameters.
	`vb`	scalar, Value of Kuiper statistic for ML parameters.
	`ve`	scalar, Value of Kuiper statistic for A2 parameters.
	`w2b`	scalar, Value of Cramer-von Mises statistic for ML parameters.
	`w2e`	scalar, Value of Cramer-von Mises statistic for A2 parameters.
	`a2b`	scalar, Value of Anderson-Darling statistic for ML parameters.
	`a2e`	scalar, Value of Anderson-Darling statistic for A2 parameters.
	`beta`	scalar, Parameter beta from MoM estimation.
	`betamin`	scalar, Parameter beta from A2 estimation.

Example:

library("xplore") library("stats") library("distribs") library("nummath") randomize(101) sample=rndexp(1000,1,3.1416) estexp(sample,0,3000)

Result:

Contents of _tmp.db
[1,]  0.013447
Contents of _tmp.de
[1,]  0.013151
Contents of _tmp.vb
[1,]  0.025864
Contents of _tmp.ve
[1,]  0.025697
Contents of _tmp.w2b
[1,]  0.025826
Contents of _tmp.w2e
[1,]  0.024666
Contents of _tmp.a2b
[1,]  0.22492
Contents of _tmp.a2e
[1,]  0.22145
Contents of _tmp.beta
[1,]   3.1631
Contents of _tmp.betamin
[1,]   3.1539

Author: A. Misiorek, 20041110 license MD*Tech