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ltsa (version 1.4.2)

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

1,653

Version

1.4.2

License

GPL (>= 2)

Maintainer

A.I. McLeod

Last Published

September 22nd, 2012

Functions in ltsa (1.4.2)

TrenchMean

Exact MLE for mean given the autocorrelation function

TrenchForecast

Minimum Mean Square Forecast

DLSimulate

Simulate linear time series

TrenchInverse

compute the matrix inverse of a positive-definite Toepliz matrix

PredictionVariance

Prediction variance

tacvfARMA

theoretical autocovariance function (acvf) of ARMA

TrenchLoglikelihood

Loglikelihood function of stationary time series using Trench algorithm

DLAcfToAR

Autocorrelations to AR parameters

DHSimulate

Simulate General Linear Process

ToeplitzInverseUpdate

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

is.toeplitz

test if argument is a symmetric Toeplitz matrix

DLLoglikelihood

Durbin-Levinsion Loglikelihood

ltsa-package

Linear time series analysis

DLResiduals

Prediction residuals

SimGLP

Simulate GLP given innovations

exactLoglikelihood

Exact log-likelihood and MLE for variance

innovationVariance

Nonparametric estimate of the innovation variance