Prints diagnostics or extract those diagnostics from a fitll object.
Object of "fitll".
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.
lldiagnostics(object) prints diagnostics or extract those diagnostics from a fitll object.
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.
Paz, R.F., Balakrishnan, N and Baz<c3><a1>n, 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.
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# 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)
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