em_tau

em_tau_safe

Supporting function for EM algorithm. Update the conditional
 probabilities of the components of the MixAR model
 (for E-step of EM algorithm).

internal

Model time series using mixture autoregressive (MAR)
models. Implemented are frequentist (EM) and Bayesian
methods for estimation, prediction and model
evaluation. See Wong and Li (2002)
<doi:10.1111/1467-9868.00222>, Boshnakov (2009)
<doi:10.1016/j.spl.2009.04.009>), and the extensive
references in the documentation.

Georgi Boshnakov

mixAR

Mixture Autoregressive Models

Davide Ravagli

em_tau function

<dl> <dt>stdetk</dt>
<dd>standardised component residuals, a <code>MixComp</code> object.</dd> <dt>prob</dt>
<dd>current estimates of the probabilities of the components, a numeric
 vector of length equal to the number of components in the model.</dd> <dt>scale</dt>
<dd>scales (standard deviations) of the noise components, a numeric
 vector of length equal to the number of components in the model.</dd> <dt>pdf</dt>
<dd>densities of the noise components.</dd></dl>

Arguments

Author

Compute probabilities for the observations to belong to each of the components — em_tau

<dl>

 <dt>stdetk</dt>
<dd>standardised component residuals, a <code>MixComp</code> object.</dd>

 <dt>prob</dt>
<dd>current estimates of the probabilities of the components, a numeric
 vector of length equal to the number of components in the model.</dd>

 <dt>scale</dt>
<dd>scales (standard deviations) of the noise components, a numeric
 vector of length equal to the number of components in the model.</dd>

 <dt>pdf</dt>
<dd>densities of the noise components.</dd>

</dl>

em_tau: Compute probabilities for the observations to belong to each of the components

Description

Usage

Arguments

Author

Details