R: Basic Bayesian Structural Time Series

cor_bsts {brms} | R Documentation

## Basic Bayesian Structural Time Series

### Description

Add a basic Bayesian structural time series component to a brms model

### Usage

    cor_bsts(formula = ~1)

### 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.

### Details

Bayesian structural time series models offer an alternative to classical AR(I)MA models (they are in fact a generalization). The basic version currently implemented in brms introduces local level terms for each observation, whereas each local level term depends on the former local level term:

LL_t ~ N(LL_{t-1}, sigmaLL)

A simple introduction can be found in this blogpost: http://multithreaded.stitchfix.com/blog/2016/04/21/forget-arima/. More complicated Bayesian structural time series models may follow in the future.

### Value

An object of class `cor_bsts`.

### Examples

    ## Not run:
    dat <- data.frame(y = rnorm(100), x = rnorm(100))
    fit <- brm(y~x, data = dat, autocor = cor_bsts())

    ## End(Not run)

[Package brms version 2.6.0 Index]