dlm: dlmModReg – R documentation

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dlm

dlmModReg

Create a DLM representation of a regression model

Description

The function creates a dlm representation of a linear regression model.

Usage

dlmModReg(X, addInt = TRUE, dV = 1, dW = rep(0, NCOL(X) + addInt),
          m0 = rep(0, length(dW)),
          C0 = 1e+07 * diag(nrow = length(dW)))

Arguments

`X`	the design matrix
`addInt`	logical: should an intercept be added?
`dV`	variance of the observation noise.
`dW`	diagonal elements of the variance matrix of the system noise.
`m0`	m0, the expected value of the pre-sample state vector.
`C0`	C0, the variance matrix of the pre-sample state vector.

Details

By setting dW equal to a nonzero vector one obtains a DLM representation of a dynamic regression model. The default value zero of dW corresponds to standard linear regression. Only univariate regression is currently covered.

Value

An object of class dlm representing the specified regression model.

Author(s)

Giovanni Petris GPetris@uark.edu

References

Giovanni Petris (2010), An R Package for Dynamic Linear Models. Journal of Statistical Software, 36(12), 1-16. http://www.jstatsoft.org/v36/i12/.
Petris, Petrone, and Campagnoli, Dynamic Linear Models with R, Springer (2009).
West and Harrison, Bayesian forecasting and dynamic models (2nd ed.), Springer, 1997.

Examples

x <- matrix(runif(6,4,10), nc = 2); x
dlmModReg(x)
dlmModReg(x, addInt = FALSE)

dlm

Bayesian and Likelihood Analysis of Dynamic Linear Models

v1.1-5

GPL (>= 2)

Authors

Giovanni Petris [aut, cre], Wally Gilks [ctb] (Author of original C code for ARMS)

Initial release

2018-05-30