Generate Posterior Simulations

Source: R/posterior.R

Generate posterior simulations for a given fitted linear or general linear model, assuming the standard "noninformative" priors on the unknowns.

posterior(obj, ...)

Arguments

obj

an object

...

further arguments

Value

A (named) list of random vectors. For example, the lm method returns a list with components sigma (the residual s.d.) and beta, the regression coefficients.

References

Kerman, J. and Gelman, A. (2007). Manipulating and Summarizing Posterior Simulations Using Random Variable Objects. Statistics and Computing 17:3, 235-244.

See also vignette("rv").

Author

Jouni Kerman jouni@kerman.com

Examples


  if (FALSE) {
  x <- 1:20
  y <- rnorm(length(x), mean=x, sd=10)
  print(summary(fit <- lm(y ~ x)))
  bayes.estimates <- posterior(fit)
  }