anova_bnp_normal: Fit a Bayesian nonparametric factorial ANOVA model with...
In igutierrezm/ANOVABNPTestR: A Bayesian Nonparametric Factorial ANOVA

anova_bnp_normal

R Documentation

Fit a Bayesian nonparametric factorial ANOVA model with Gaussian kernel

Description

Fit a Bayesian nonparametric factorial ANOVA model with Gaussian kernel

Usage

anova_bnp_normal(
  y,
  X,
  iter = 4000L,
  warmup = 2000L,
  seed = 1L,
  n = 50L,
  rho = 1,
  a = 1,
  b = 1,
  a0 = 2,
  lambda0 = 1,
  mu0 = 0,
  b0 = 1,
  lb = mean(y) - 3 * sd(y),
  ub = mean(y) + 3 * sd(y),
  standardize_y = FALSE
)

Arguments

`y`	a continuous response vector.
`X`	a design matrix (full of integer covariates).
`iter`	the total number of mcmc iterations.
`warmup`	the number of warmup mcmc iterations.
`seed`	the seed for random number generation.
`n`	the number of points `y_0` for computing `p(y_0 \| y)`. The final grid is conformed by `n` equispaced points from `lb` to `ub`, see the arguments `lb` and `ub`.
`rho`	the hyperparameter `\rho`.
`a`	the hyperparameter `a`.
`b`	the hyperparameter `b`.
`a0`	the hyperparameter `a_0`.
`lambda0`	the hyperparameter `\lambda_0`.
`mu0`	the hyperparameter `\mu_0`.
`b0`	the hyperparameter `b_0`.
`lb`	the lower bound of the prediction grid.
`ub`	the upper bound of the prediction grid.
`standardize_y`	Select `TRUE` to internally standardize the data, fit the model, and present the results in the original scale.