Modelagem de Regressão Bayesiana com rstanarm
Jake Thompson
Psychometrician, ATLAS, University of Kansas
stan_model <- stan_glm(kid_score ~ mom_iq, data = kidiq,
prior_intercept = normal(location = 0, scale = 10),
prior = normal(location = 0, scale = 2.5),
prior_aux = exponential(rate = 1)
)
stan_model <- stan_glm(kid_score ~ mom_iq, data = kidiq,
prior_intercept = normal(location = 0, scale = 10, autoscale = FALSE),
prior = normal(location = 0, scale = 2.5, autoscale = FALSE),
prior_aux = exponential(rate = 1, autoscale = FALSE)
)
stan_model <- stan_glm(kid_score ~ mom_iq, data = kidiq,
prior_intercept = normal(location = 3, scale = 2),
prior = cauchy(location = 0, scale = 1))
normal()exponential()student_t()cauchy()?priorsstan_model <- stan_glm(kid_score ~ mom_iq, data = kidiq,
prior_intercept = NULL,
prior = NULL,
prior_aux = NULL)
prior_summary(stan_model)
Priors para o modelo 'stan_model'
------
Intercepto (após centralizar preditores)
~ plano
Coeficientes
~ plano
Auxiliar (sigma)
~ plano
------
Veja help('prior_summary.stanreg') para mais detalhes
Modelagem de Regressão Bayesiana com rstanarm