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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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Install
install.packages('ltsa')
Monthly Downloads
1,236
Version
1.4.2
License
GPL (>= 2)
Maintainer
A.I. McLeod
Last Published
September 22nd, 2012
Functions in ltsa (1.4.2)
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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