ltsa v1.4.6
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Linear Time Series Analysis
Methods of developing linear time series modelling.
Methods are given for loglikelihood computation, forecasting
and simulation.
Functions in ltsa
| Name | Description | |
| 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 | |
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Details
| Date | 2015-12-20 |
| Classification/ACM | G.3, G.4, I.5.1 |
| Classification/MSC | 62M10, 91B84 |
| License | GPL (>= 2) |
| URL | http://www.stats.uwo.ca/faculty/aim |
| NeedsCompilation | yes |
| Packaged | 2015-12-21 02:25:34 UTC; IanMcLeod |
| Repository | CRAN |
| Date/Publication | 2015-12-21 08:55:04 |
| depends | base (>= 2.1.0) , R (>= 2.1.0) |
| Contributors | A.I. McLeod, Hao Yu, Zinovi Krougly |
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