Specifies the information required to fit a Negative Binomial GLM in a
similar way to negative.binomial. However, here the
overdispersion parameter theta is not specified by the user and always
estimated (really the reciprocal of the dispersion parameter is
estimated). A call to this function can be passed to the family
argument of stan_glm or stan_glmer to estimate a
Negative Binomial model. Alternatively, the stan_glm.nb and
stan_glmer.nb wrapper functions may be used, which call
neg_binomial_2 internally.
Arguments
- link
The same as for
poisson, typically a character vector of length one among"log","identity", and"sqrt".
Examples
if (.Platform$OS.type != "windows" || .Platform$r_arch != "i386")
stan_glm(Days ~ Sex/(Age + Eth*Lrn), data = MASS::quine, seed = 123,
family = neg_binomial_2, QR = TRUE, algorithm = "optimizing")
#> stan_glm
#> family: neg_binomial_2 [log]
#> formula: Days ~ Sex/(Age + Eth * Lrn)
#> observations: 146
#> predictors: 14
#> ------
#> Median MAD_SD
#> (Intercept) 3.1 0.3
#> SexM -0.5 0.4
#> SexF:AgeF1 -0.8 0.3
#> SexM:AgeF1 -0.7 0.3
#> SexF:AgeF2 -0.6 0.4
#> SexM:AgeF2 0.6 0.3
#> SexF:AgeF3 -0.4 0.4
#> SexM:AgeF3 1.1 0.4
#> SexF:EthN -0.1 0.3
#> SexM:EthN -0.7 0.3
#> SexF:LrnSL 1.0 0.3
#> SexM:LrnSL 0.2 0.4
#> SexF:EthN:LrnSL -1.4 0.4
#> SexM:EthN:LrnSL 0.8 0.5
#>
#> Auxiliary parameter(s):
#> Median MAD_SD
#> reciprocal_dispersion 1.4 0.2
#>
#> ------
#> * For help interpreting the printed output see ?print.stanreg
#> * For info on the priors used see ?prior_summary.stanreg
# or, equivalently, call stan_glm.nb() without specifying the family