RDocumentation
Moon
Learn R
Search all packages and functions
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.
Copy Link
Copy
Link to current version
Version
Version
1.4.6
1.4.5
1.4.4
1.4.2
1.3
1.1
1.0
Down Chevron
Install
install.packages('ltsa')
Monthly Downloads
1,147
Version
1.4.6
License
GPL (>= 2)
Maintainer
A.I. McLeod
Last Published
December 21st, 2015
Functions in ltsa (1.4.6)
Search functions
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