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ltsa (version 1.4.6.1)
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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1.4.6.1
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Install
install.packages('ltsa')
Monthly Downloads
1,664
Version
1.4.6.1
License
GPL (>= 2)
Maintainer
A.I. McLeod
Last Published
September 18th, 2024
Functions in ltsa (1.4.6.1)
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innovationVariance
Nonparametric estimate of the innovation variance
exactLoglikelihood
Exact log-likelihood and MLE for variance
tacvfARMA
theoretical autocovariance function (acvf) of ARMA
SimGLP
Simulate GLP given innovations
DLLoglikelihood
Durbin-Levinsion Loglikelihood
DLResiduals
Prediction residuals
DLAcfToAR
Autocorrelations to AR parameters
PredictionVariance
Prediction variance
DHSimulate
Simulate General Linear Process
DLSimulate
Simulate linear time series
ToeplitzInverseUpdate
Inverse of Toeplitz matrix of order n+1 given inverse of order n
TrenchLoglikelihood
Loglikelihood function of stationary time series using Trench algorithm
TrenchInverse
compute the matrix inverse of a positive-definite Toepliz matrix
is.toeplitz
test if argument is a symmetric Toeplitz matrix
ltsa-package
Linear Time Series Analysis
TrenchMean
Exact MLE for mean given the autocorrelation function
TrenchForecast
Minimum Mean Square Forecast