init_lm_gprior: Initialize linear regression parameters assuming a g-prior

In countSTAR: Flexible Modeling of Count Data

Initialize linear regression parameters assuming a g-prior

Description

Initialize the parameters for a linear regression model assuming a g-prior for the coefficients.

Usage

init_lm_gprior(y, X, X_test = NULL)

Arguments

y	n x 1 vector of data
X	n x p matrix of predictors
X_test	n0 x p matrix of predictors at test points (default is NULL)

Value

a named list params containing at least

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

2. sigma: the conditional standard deviation

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

Additionally, if X_test is not NULL, then the list includes an element mu_test, the vector of conditional means at the test points

Note

The parameters in coefficients are:

• beta: the p x 1 vector of regression coefficients components of beta

Examples

# Simulate data for illustration:
sim_dat = simulate_nb_lm(n = 100, p = 5)
y = sim_dat$y; X = sim_dat$X

# Initialize:
params = init_lm_gprior(y = y, X = X)
names(params)
names(params$coefficients)

countSTAR documentation built on July 9, 2023, 5:12 p.m.