CopulaDTA (version 0.0.2)

forestplot.cdtafit: Produce forest plots for categorical covariates.

Description

Produce forest plots for categorical covariates.

Usage

forestplot.cdtafit(x, title.1 = NULL, title.2 = NULL, title.3 = NULL,
  graph = NULL, width = 0.2, shape.1 = 19, size.1 = 2.5, shape.2 = 8,
  size.2 = 2.5, shape.O = 9, size.O = 3.5, cols.1 = NULL,
  cols.2 = NULL, digits = 3, ...)

Value

Forestplots by ggplot2.

References

{Watanabe S (2010). Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory. Journal of Machine Learning Research, 11, 3571-3594.}

{Vehtari A, Gelman A (2014). WAIC and Cross-validation in Stan. Unpublished, pp. 1-14.}

Examples

fit1 <- fit(data=telomerase,
             SID = "ID",
             copula="fgm",
             iter = 400,
             warmup = 100,
             seed=1,
             cores=1)

plot(fit1)