rjmonopoly: Reversible jump sampler for monotonic polynomials

In hhau/rjmonopoly: Order Selection of Monotonic Polynomials via Reversible Jump

Description

Other notes

Usage

rjmonopoly(x, y, d_min = 2, d_max = 10, iter = 50000, prior_option = NA,
  prior_prob = 0.5, starting_var_val = 0.001, control = list(innov_sd_beta
  = 0.025, innov_sd_var = 0.025), progress = TRUE)

Arguments

x	vector of x values
y	vector of y values
d_min	minimum allowable polynomial degree
d_max	maximum allowable polynomial degree
iter	number of iterations
prior_option	if NA is replaced with the string: "flat", then a flat prior for the variance will be used instead of a pseudo binomial prior.
prior_prob	probability for binomial prior
starting_var_val	starting value for variance
control	(optional) list of innovation variances
progress	turn the progress bar on / off. TRUE is the default, and will show the progress bar.

Details

Note that the samples for Gamma and Sigma^2 are on the orthonormal scale.

Value

object of type rjmonopol_fit containing lists of samples for all regression parameters

Examples

## Not run: 
library(fda)
x <- onechild$day
y <- onechild$height
fit <- rjmonopoly(x, y)

## End(Not run)

hhau/rjmonopoly documentation built on May 17, 2019, 4:01 p.m.