fDMA (version 2.2.8)

grid.tvp: Computes tvp Function for Multiple Values of lambda.

Description

Sometimes it is necessary to consider various values of parameter lambda in Time-Varying Parameters Regression. This function computes tvp function for all values of lambda for a given grid.

This function is a wrapper of tvp.

Usage

grid.tvp(y,x,V,grid.lambda,W=NULL,kappa=NULL,parallel.grid=NULL,c=NULL)

Value

an object of class grid.tvp, list of

$models

list of tvp objects

$fq

matrix with Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) for all estimated models

Arguments

y

see tvp

x

see tvp

V

see tvp

grid.lambda

a numeric vector of different values of lambda, see tvp

W

optional, see tvp

kappa

optional, see tvp

parallel.grid

optional, logical, indicate whether parallel computations should be used, by default parallel=FALSE

c

optional, see tvp

See Also

print.grid.tvp, summary.grid.tvp, plot.grid.tvp.

Examples

wti <- crudeoil[-1,1]
drivers <- (lag(crudeoil[,-1],k=1))[-1,]
ld.wti <- (diff(log(wti)))[-1,]
ld.drivers <- drivers[-1,]
ld.drivers[,c(4,6)] <- (diff(drivers[,c(4,6)]))[-1,]
ld.drivers[,c(1:2,5,7)] <- (diff(log(drivers[,c(1:2,5,7)])))[-1,]
ld.drivers[,c(3,6)] <- ld.drivers[,c(3,6)]/100
# \donttest{
grl <- c(0.99,0.98,0.97,0.96,0.95)
g <- grid.tvp(y=ld.wti,x=ld.drivers,V=1,grid.lambda=grl)

# extract model with lambda=0.95
model <- g$models[[5]]
# }