dlmModPoly: Create an n-th order polynomial DLM

In dlm: Bayesian and Likelihood Analysis of Dynamic Linear Models

Description

The function creates an n-th order polynomial DLM.

Usage

dlmModPoly(order = 2, dV = 1, dW = c(rep(0, order - 1), 1),
           m0 = rep(0, order), C0 = 1e+07 * diag(nrow = order)) 

Arguments

order	order of the polynomial model. The default corresponds to a stochastic linear trend.
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.

Value

An object of class dlm representing the required n-th order polynomial 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. 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.

See Also

dlmModARMA, dlmModReg, dlmModSeas

Examples

## the default
dlmModPoly()
## random walk plus noise
dlmModPoly(1, dV = .3, dW = .01)

Example output

$FF
     [,1] [,2]
[1,]    1    0

$V
     [,1]
[1,]    1

$GG
     [,1] [,2]
[1,]    1    1
[2,]    0    1

$W
     [,1] [,2]
[1,]    0    0
[2,]    0    1

$m0
[1] 0 0

$C0
      [,1]  [,2]
[1,] 1e+07 0e+00
[2,] 0e+00 1e+07

$FF
     [,1]
[1,]    1

$V
     [,1]
[1,]  0.3

$GG
     [,1]
[1,]    1

$W
     [,1]
[1,] 0.01

$m0
[1] 0

$C0
      [,1]
[1,] 1e+07

dlm documentation built on May 2, 2019, 4:58 p.m.