summary: Calculate summary statistics for 'mobility.model' class

In COVID-19-Mobility-Data-Network/mobility: Tools for Analyzing Human Mobility Data

Description

This is a wrapper function of MCMCsummary that calculates summary statistics for each parameter in a mobility.model object. Summary statistics are calculated for all parameters across each chain along with convergance diagnosics like the Gelman-Rubin convergence diagnostic and (Rhat) and samples auto-correlation foreach parameter. If the model object contains deviance and penalty parameters, then Deviance Information Criterion (DIC) is calculated and appended to the summary.

Usage

summary(object, probs, ac_lags, ...)

Arguments

object	a mobility.model object (can also accept a mcmc.list object)
probs	numeric vector giving the quantiles to calculate for each parameter (default = c(0.025, 0.5, 0.975))
ac_lags	numeric vector of lags over which to calculate autocorrelation of samples within chains (default = c(2,5,10))
...	further arguments passed to or from other methods

Value

a dataframe with summary statistics

Author(s)

John Giles

See Also

Other model: check(), compare(), fit_jags(), fit_prob_travel(), mobility(), predict(), residuals()

Examples

mod <- mobility(data=mobility_matrices, model='gravity', type='transport', DIC=TRUE)
summary(mod)

COVID-19-Mobility-Data-Network/mobility documentation built on Nov. 22, 2021, 12:17 a.m.