print.pandemicEstimated: Print method for 'pandemicEstimated' objects

In PandemicLP: Long Term Prediction for Epidemic and Pandemic Data

Print method for pandemicEstimated objects

Description

The print method for pandemicEstimated object of class S3 displays a compact summary of the fitted model. See the Details section below for descriptions of the different components of the printed output. For additional summary statistics and diagnostics use summary.pandemicEstimated.

Usage

## S3 method for class 'pandemicEstimated'
print(x, digits = 3, probs = c(0.025, 0.5, 0.975), info = TRUE, ...)

Arguments

x	an object of S3 class pandemicEstimated-objects.
digits	Number of digits to use for formatting numbers.
probs	a numeric vector of quantiles of interest. The default is c(0.025,0.5,0.975).
info	TRUE or FALSE: more details for output interpretation. The Default is TRUE.
...	currently unused.

Details

Point estimates

Regardless of the estimation algorithm, point estimates are mean and (or) quantiles computed from simulations. For models fit using MCMC ("sampling", this is default algorithim of pandemic_model function), the posterior sample is used. For others estimation algorithm see sampling (rstan package).

Convergence and efficiency diagnostics for Markov Chains

Included in the print are: split effective sample sizes (n_eff) and split Rhats.

The R-hat convergence diagnostic compares the between- and within-chain estimates for model parameters and other univariate quantities of interest. If chains have not mixed well (ie, the between- and within-chain estimates don't agree), R-hat is larger than 1. We recommend running at least four chains by default and only using the sample if R-hat is less than 1.05.

Priors

A list with information about the prior distributions used and model restrictions (if there are any). For more information go to models.

Value

Returns x, invisibly.

See Also

summary.pandemicEstimated.

PandemicLP documentation built on March 18, 2022, 6:22 p.m.