information_arma

Fortran implementation of <code>InformationMatrixARMA</code> function of
<code>FitARMA</code> package, except that the function uses the same
ARMA model definition as <code>arima</code>, where both the
AR and MA parts of the model are on the right side of the equation, i.e.
MA coefficients differ in sign compared to <code>InformationMatrixARMA</code>.

Prediction intervals for ARIMA and structural time series
models using importance sampling approach with uninformative priors for model
parameters, leading to more accurate coverage probabilities in frequentist
sense. Instead of sampling the future observations and hidden states of the
state space representation of the model, only model parameters are sampled,
and the method is based solving the equations corresponding to the conditional
coverage probability of the prediction intervals. This makes method relatively
fast compared to for example MCMC methods, and standard errors of prediction
limits can also be computed straightforwardly.

Jouni Helske

tsPI

Improved Prediction Intervals for ARIMA Processes and Structural
Time Series

information_arma function

<dl><dt>phi</dt>
<dd>Autoregressive coefficients.</dd>
<dt>theta</dt>
<dd>Moving average coefficients.</dd></dl>

Arguments

Large Sample Approximation of Information Matrix for ARMA process — information_arma

<dl>

<dt>phi</dt>
<dd>Autoregressive coefficients.</dd>


<dt>theta</dt>
<dd>Moving average coefficients.</dd>

</dl>

information_arma: Large Sample Approximation of Information Matrix for ARMA process

Description

Usage

Value

Arguments

References