R arm of morie.fn.bamse, bypvl and nocse. Bamse:
posterior standard deviations (n - 1 denominator) of each column of an MCMC
chain. Bypvl: posterior predictive p-value, the share of replicated
test statistics at or above the observed one. Nocse: normal
confidence half-widths z times the bootstrap standard errors of NOMINATE
estimates.
Usage
Bamse(chain)
Bypvl(chain, test_stat)
Nocse(boot_se, alpha = 0.05)
Arguments
- chain
MCMC draws (rows) by parameter (columns), or replicated statistics.
- test_stat
Observed test statistic.
- boot_se
Bootstrap standard errors.
- alpha
Error rate.
Value
A named list (the Python result's fields).
References
Gelman, A., Meng, X.-L. and Stern, H. (1996). Posterior predictive assessment of model fitness via realized discrepancies. Statistica Sinica 6, 733-807.
Poole, K. T. and Rosenthal, H. (1997). Congress: A Political-Economic History of Roll Call Voting. Oxford University Press.
Examples
Bamse(cbind(c(1, 2, 4), c(5, 3, 4)))$ses
#> [1] 1.527525 1.000000
Bypvl(c(0.2, 1.5, 0.9, 2.2, 1.1), 1)$value
#> [1] 0.6
