countSTAR (version 1.0.2)

sample_bam_orthog: Sample the parameters for an additive model

Description

Sample the parameters for an additive model, which may contain both linear and nonlinear predictors. The nonlinear terms are modeled using orthogonalized splines. The sampler draws the linear terms jointly and then samples each vector of nonlinear coefficients using Bayesian backfitting (i.e., conditional on all other nonlinear and linear terms).

Usage

sample_bam_orthog(
  y,
  X_lin,
  X_nonlin,
  params,
  A = 10^4,
  B_all = NULL,
  diagBtB_all = NULL,
  XtX = NULL
)

Value

The updated named list params with draws from the full conditional distributions of sigma and coefficients (and updated mu).

Arguments

y

n x 1 vector of data

X_lin

n x pL matrix of predictors to be modelled as linear

X_nonlin

n x pNL matrix of predictors to be modelled as nonlinear

params

the named list of parameters containing

1. mu: vector of conditional means (fitted values)

2. sigma: the conditional standard deviation

3. coefficients: a named list of parameters that determine mu

A

the prior scale for sigma_beta, which we assume follows a Uniform(0, A) prior.

B_all

optional pNL-dimensional list of n x L[j] dimensional basis matrices for each nonlinear term j=1,...,pNL; if NULL, compute internally

diagBtB_all

optional pNL-dimensional list of diag(crossprod(B_all[[j]])); if NULL, compute internally

XtX

optional p x p matrix of crossprod(X) (one-time cost); if NULL, compute internally