partialAR v1.0.3

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by Matthew Clegg

Partial Autoregression

Fits time series models which consist of a sum of a permanent and a transient component.

Functions in partialAR

Name Description
kalman.gain.par Kalman gain matrix of the partially autoregressive model
loglik.par Negative log likelihood of a partially autoregressive fit
rpar Random partially autoregressive sequence
sample.likelihood_ratio.par Generates random samples of the likelihood ratio for the partially autoregressive model
statehistory.par Estimates hidden states of a partially autoregressive model
partialAR-package Partial autoregression
as.data.frame.par.fit Convert a fit of the PAR model to a single row data.frame
fit.par Fit a partially autoregressive model
test.par Likelihood ratio test for partially autoregressive model
estimate.par Estimates the parameters of a partially autoregressive fit using lagged variances
likelihood_ratio.par Computes log likelihood ratio for partial autoregressive model
which.hypothesis.partest Returns the preferred hypothesis when testing for partial autoregression
pvmr.par Proportion of variance attributable to mean reversion
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Details

Type Package
Date 2015-01-12
License GPL-2 | GPL-3
LinkingTo Rcpp
Packaged 2015-01-28 22:43:42 UTC; matthewclegg
NeedsCompilation yes
Repository CRAN
Date/Publication 2015-01-29 00:25:11

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