Installation

# install.packages("devtools")devtools::install_github("fndemarqui/bellreg")

Example

library(bellreg)data(faults)# ML approach:mle<- bellreg(nf~lroll,data=faults,approach="mle",init=0)summary(mle)#> Call:#> bellreg(formula = nf ~ lroll, data = faults, approach = "mle",#>     init = 0)#>#> Coefficients:#>               Estimate     StdErr z.value   p.value#> (Intercept) 0.98524220 0.33219474  2.9659  0.003018 **#> lroll       0.00190934 0.00049004  3.8963 9.766e-05 ***#> ---#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#>#> logLik = -88.96139   AIC = 181.9228# Bayesian approach:bayes<- bellreg(nf~lroll,data=faults,approach="bayes",refresh=FALSE)summary(bayes)#>#> bellreg(formula = nf ~ lroll, data = faults, approach = "bayes",#>     refresh = FALSE)#>#>              mean se_mean    sd  2.5%   25%   50%   75% 97.5%    n_eff  Rhat#> (Intercept) 0.984   0.007 0.334 0.331 0.758 0.978 1.213 1.627 2222.313 1.001#> lroll       0.002   0.000 0.000 0.001 0.002 0.002 0.002 0.003 2478.992 1.001#>#> Inference for Stan model: bellreg.#> 4 chains, each with iter=2000; warmup=1000; thin=1;#> post-warmup draws per chain=1000, total post-warmup draws=4000.