cor_ar: AR(p) correlation structure

Description

This function is a constructor for the cor_arma class, allowing for autoregression terms only.

Usage

cor_ar(formula = ~1, p = 1, cov = FALSE)

Arguments

formula

A one sided formula of the form ~ t, or ~ t | g, specifying a time covariate t and, optionally, a grouping factor g. A covariate for this correlation structure must be integer valued. When a grouping factor is present in formula, the correlation structure is assumed to apply only to observations within the same grouping level; observations with different grouping levels are assumed to be uncorrelated. Defaults to ~ 1, which corresponds to using the order of the observations in the data as a covariate, and no groups.

A non-negative integer specifying the autoregressive (AR) order of the ARMA structure. Default is 0.

cov

A flag indicating whether ARMA effects should be estimated by means of residual covariance matrices (currently only possible for stationary ARMA effects of order 1). If FALSE (the default) a regression formulation is used that is considerably faster and allows for ARMA effects of order higher than 1 but cannot handle user defined standard errors.

Value

An object of class cor_arma containing solely autoregression terms.

Details

As of brms version 0.6.0, the AR structure refers to autoregressive effects of residuals to match the naming and implementation in other packages such as nlme. Previously, the AR term in brms referred to autoregressive effects of the response. The latter are now named ARR effects and can be modeled using argument r in the cor_arma and cor_arr functions.

Examples

Run this code

cor_ar(~visit|patient, p = 2)