tsDyn (version 11.0.4.1)

selectHyperParms: Automatic selection of model hyper-parameters

Description

Automatic selection of model hyper-parameters

Usage

selectLSTAR(x, m, d=1, steps=d, mL = 1:m, mH = 1:m, thDelay=0:(m-1), 
            fast=TRUE, trace=FALSE)
selectNNET(x, m, d=1, steps=d, size=1:(m+1), maxit=1e3, trace=FALSE)

Value

A data-frame, with columns giving hyper-parameter values and the computed AIC for each row (only the best 10s are returned)

Arguments

x

time series

m, d, steps

embedding parameters. For their meanings, see help about nlar

mL,mH

Vector of ‘low’ and ‘high’ regimes autoregressive orders

thDelay

Vector of ‘threshold delay’ values

size

Vector of numbers of hidden units in the nnet model

maxit

Max. number of iterations for each model estimation

fast

For LSTAR selection, whether a fast algorithm using starting values fro previous models should be used

trace

Logical. Whether informations from each model should be returned.

Author

Antonio, Fabio Di Narzo

Details

Functions for automatic selection of LSTAR and NNET models hyper parameters. An exhaustive search over all possible combinations of values of specified hyper-parameters is performed. Embedding parameters m,d,steps are kept fixed.

Selection criterion is the usual AIC.

For the LSTAR model, two methods are offered:

fast=FALSE

Each model is run separately, each time using the full grid search for starting values.

fast=TRUE

Only the first model is run with a full grid search, while the subsequent use the first model results for their starting values.

Examples

llynx <- log10(lynx)
selectLSTAR(llynx, m=2)
selectNNET(llynx, m=3, size=1:5)