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ltsa (version 1.4.6)

Linear Time Series Analysis

Description

Methods of developing linear time series modelling. Methods are given for loglikelihood computation, forecasting and simulation.

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Version

Install

install.packages('ltsa')

Monthly Downloads

1,413

Version

1.4.6

License

GPL (>= 2)

Maintainer

A.I. McLeod

Last Published

December 21st, 2015

Functions in ltsa (1.4.6)

DLAcfToAR

Autocorrelations to AR parameters

DLResiduals

Prediction residuals

TrenchInverse

compute the matrix inverse of a positive-definite Toepliz matrix

TrenchMean

Exact MLE for mean given the autocorrelation function

PredictionVariance

Prediction variance

innovationVariance

Nonparametric estimate of the innovation variance

DLLoglikelihood

Durbin-Levinsion Loglikelihood

TrenchLoglikelihood

Loglikelihood function of stationary time series using Trench algorithm

SimGLP

Simulate GLP given innovations

ToeplitzInverseUpdate

Inverse of Toeplitz matrix of order n+1 given inverse of order n

TrenchForecast

Minimum Mean Square Forecast

is.toeplitz

test if argument is a symmetric Toeplitz matrix

tacvfARMA

theoretical autocovariance function (acvf) of ARMA

DHSimulate

Simulate General Linear Process

exactLoglikelihood

Exact log-likelihood and MLE for variance

ltsa-package

Linear Time Series Analysis

DLSimulate

Simulate linear time series