Calculate summary statistics for 'mobility.model' class

Source: R/summary.R

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.

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

See also

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

Author

John Giles

Examples

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

#> ::Fitting transport gravity model for 10 origins and 10 destinations::
#> Compiling model graph
#>    Resolving undeclared variables
#>    Allocating nodes
#> Graph information:
#>    Observed stochastic nodes: 70
#>    Unobserved stochastic nodes: 32
#>    Total graph size: 417
#> 
#> Initializing model
#> 
#> NOTE: Stopping adaptation
#> 
#> 
summary(mod)

#>                  mean           sd         Q2.5        Q97.5 Rhat n.eff   AC5
#> gamma    1.816561e-01 6.120037e-04 1.803954e-01 1.827982e-01 1.00  1089  0.04
#> theta    1.541606e-05 6.110462e-08 1.530066e-05 1.553273e-05 1.00  1882 -0.02
#> DIC      4.931091e+04 1.863001e+00 4.930903e+04 4.931594e+04 1.02  1028  0.05
#> deviance 4.930703e+04 1.863001e+00 4.930515e+04 4.931206e+04 1.02  1028  0.05
#> pD       1.939190e+00           NA           NA           NA   NA    NA    NA
#>           AC10
#> gamma     0.02
#> theta    -0.01
#> DIC       0.01
#> deviance  0.01
#> pD          NA