optimise_EXPAR {EXPAR}

Fitting of EXPAR model with given order

Description

Fits an EXPAR model of given order to the data by RSS minimisation

Usage

optimise_EXPAR(ts_data, order, init, opt_method = "BFGS")

Arguments

ts_data

A univarite time series data, to which an EXPAR model of given order is to be fitted.

order

Order p of the EXPAR model to be considered.

init

The initial values for optimisation. If omitted, initial values are decided using initial_val().

opt_method

The optimization algorithm to be used for RSS minimization. Corresponds to arguments from optim() in stats library. Defaults to the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm.

Details

This function estimates the parameters an EXPAR(p) model by minimizing RSS and returns a fit with the optimised parameters. The fit is returned using the function fit_EXPAR(), with the parameters inputted being the optimized ones. Available optimisation techniques include possible arguments from method in optim().

Value

Returns the fitted EXPAR model as a list with the following components,

series

The data used for fitting the model.

order

Order p of the fitted EXPAR model.

n

Number of observations in series.

k

Number of parameters in the model.

par

Parameters of the fitted model.

Fitted

Fitted values obtained from the model.

Residuals

Residuals of the fitted model.

RSS

The residual sum of squares.

AIC

Akaike information criterion, evaluated from RSS.

AIC_c

Corrected Akaike information criterion, evaluated from RSS.

BIC

Bayesian information criterion, evaluated from RSS.

counts

counts returned by optim()

convergence

convergence returned by optim()

message

message returned by optim()

Examples

datats <- ts(egg_price_index[,3], start = c(2013, 1), frequency = 12)
optimise_EXPAR(datats, 2, opt_method = "BFGS")