lldiagnostics {llbayesireg}

Diagnostics from a fitll object

Description

Prints diagnostics or extract those diagnostics from a fitll object.

Usage

lldiagnostics(object)

Arguments

object

Object of "fitll".

Details

The function calls the check_* functions and the get_* functions are for access to the diagnostics. If the matrix X and W are missing, the coda package is used by test the convergence of the chains by Cramer-von-Mises statistic and an image of the correlation is show for both of generated chains.

Value

lldiagnostics(object) prints diagnostics or extract those diagnostics from a fitll object.

Author(s)

Sara Alexandre Fonsêca [e-mail], Rosineide Fernando da Paz [e-mail], Jorge Luís Bazán

Source

The L-Losgistic distribution was introduced by Tadikamalla and Johnson (1982), which refer to this distribution as Logit-Logistic distribution. Here, we have a new parameterization of the Logit-Logistic with the median as a parameter.

References

Paz, R.F., Balakrishnan, N and Bazán, J.L. (2018). L-Logistic Distribution: Properties, Inference and an Application to Study Poverty and Inequality in Brazil. The Stan Development Team Stan Modeling Language User's Guide and Reference Manual. http://mc-stan.org/. Plummer, M., Best, N., Cowles, K., and Vines, K. (2006). Coda: Convergence diagnosis and output analysis for mcmc. R News, 6(1):7-11.

Examples

# Modelation the coeficient with generated data

library(llbayesireg)
library(llogistic)

# Number of elements to be generated

n=50

# Generated response

bin=2005
set.seed(bin)
y=rllogistic(n,0.5, 2)

fitll = llbayesireg(y, niter=100, jump=10)

lldiagnostics(fitll$object)
 
# Modelation the coeficient with real data
library(llbayesireg)

data("Votes","MHDI")

y = Votes[,4]
X = MHDI

fitll = llbayesireg(y,X)

lldiagnostics(fitll$object)