L: Lag function for autoregressive models

In bayesGAM: Fit Multivariate Response Generalized Additive Models using Hamiltonian Monte Carlo

Lag function for autoregressive models

Description

Creates lagged variables for use with bayesGAM, including the functionality to create lags for each specified subject if desired. The input data must be pre- sorted according by time, and within each subject id if specified.

Usage

L(x, k = 1, id = NULL)

Arguments

x	numeric vector
k	integer vector of lagged variables to create
id	optional identification number for each subject

Value

numeric vector or matrix of the lagged variable(s)

References

Zeileis A (2019). dynlm: Dynamic Linear Regression. R package version 0.3-6

Examples

x <- rnorm(20)
id <- rep(1:4, each=5)
L(x, 1:2, id)

# autoregressive
ar.ols(lh, demean = FALSE, intercept=TRUE, order=1)
f <- bayesGAM(lh ~ L(lh), family=gaussian)
coef(f)

bayesGAM documentation built on March 18, 2022, 6:29 p.m.