tsDyn (version 0.9-1)

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)

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.

Value

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

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: [object Object],[object Object]

Examples

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