bkmrdlm_multi_polynomial: Estimates the BKMR-DLM for a multiple time-varying predictor.

In AnderWilson/regimes: Regression in Multivariate Exposure Settings

Estimates the BKMR-DLM for a multiple time-varying predictor.

Description

Estimates the BKMR-DLM for a multiple time-varying predictor.

Usage

bkmrdlm_multi_polynomial(
  yz,
  Xlist,
  b1,
  a1,
  a2,
  kappa,
  n_inner,
  n_outer,
  n_burn,
  d
)

Arguments

yz	a matrix that is cbind(y,Z) where Z is a matrix of covariates that does not include an intercept and y is the vector of outcomes.
Xlist	a list of matrices each for a single exposure in time order.
b1	first parameter for prior on tau^-2 in the text.
a1	first parameter for prior on sigma^-2.
a2	second parameter for prior on sigma^-2.
kappa	scale parameter, rho/kappa~chisq(1).
n_inner	number of MCMC iterations to run in the inner loop. This is equivelent the the thinning number. n_outer*n_inner iteraction will be run and n_outer iterations will be saved.
n_outer	number of MCMC iteration in the outer loop. The output for each is saved.
n_burn	number of MCMC iteration to be discarded as burn-in.
d	the degree of polynomial for a polynomial kernel.

AnderWilson/regimes documentation built on Aug. 5, 2023, 8:30 a.m.