dlmModReg: Create a DLM representation of a regression model

In dlm: Bayesian and Likelihood Analysis of Dynamic Linear Models

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	m_0, the expected value of the pre-sample state vector.
C0	C_0, 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 [e-mail]

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.

See Also

dlmModARMA, dlmModPoly, dlmModSeas

Examples

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

dlm documentation built on Sept. 21, 2024, 9:06 a.m.