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)))

Value

An object of class dlm representing the specified regression model.

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: $m_{0}$ , the expected value of the pre-sample state vector.
C0: $C_{0}$ , the variance matrix of the pre-sample state vector.

Author

Giovanni Petris GPetris@uark.edu

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.

References

Giovanni Petris (2010), An R Package for Dynamic Linear Models. Journal of Statistical Software, 36(12), 1-16. https://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

Run this code

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

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