TSMN: TSMN: Truncated Scale Mixtures of Normal Distributions

Description Author(s) References See Also Examples

Description

This package includes two functions related to the truncated scale mixtures of normal distribution. One of then is to generate random samples from TSMN distribution, and other is to compute the first four theoretical moments.

Author(s)

Eraldo B. dos Anjos Filho ebdaf1@de.ufpe.br and Aldo M. Garay agaray@de.ufpe.br

Maintainer: Eraldo B. dos Anjos Filho ebdaf1@de.ufpe.br

References

Aldo M. Garay, Victor H. Lachos, Heleno Bolfarine, Celso R. Cabral. "Linear censored regression models with scale mixtures of normal distributions". Statistical Papers, 2017, vol. 58, issue 1, pages 247-278

See Also

TSMNmoments,TSMNgenerator

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
 ## A test sample to compare theoretical and empirical moments, considering the following parameters:

 mu = 2
 sigma2 = 4
 nu = 5
 lower = -3
 upper = 10
 dist = "T"
 n = 10000

 ## Theoretical moments with TSMNmoments
 theor<-TSMNmoments(mu=mu, sigma2=sigma2, nu=nu, lower=lower, upper=upper, dist=dist)

 ## Generate the sample with TSMNgenerator to compute the empirical moments
 empir<-TSMNgenerator(n=n, mu=mu, sigma2=sigma2, nu=nu, lower=lower, upper=upper, dist=dist)

 ## Compare the results
 data.frame("1st" = c("Theoretic" = theor$EY1, "Empirical" = mean(empir)),
            "2nd" = c("Theoretic" = theor$EY2, "Empirical" = mean(empir^2)),
            "3rd" = c("Theoretic" = theor$EY3, "Empirical" = mean(empir^3)),
            "4th" = c("Theoretic" = theor$EY4, "Empirical" = mean(empir^4)))

EBDAF1/TSMN documentation built on May 23, 2019, 10:32 p.m.