logLik.refitME

Extract log-Likelihoods for <code>refitME</code> model objects. This function subtracts the entropy term from the observed likelihood.

Fits measurement error models using Monte Carlo Expectation Maximization (MCEM). For specific details on the methodology, see: Greg C. G. Wei & Martin A. Tanner (1990) A Monte Carlo Implementation of the EM Algorithm and the Poor Man's Data Augmentation Algorithms, Journal of the American Statistical Association, 85:411, 699-704 <doi:10.1080/01621459.1990.10474930> For more examples on measurement error modelling using MCEM, see the 'RMarkdown' vignette: "'refitME' R-package tutorial".

Jakub Stoklosa

refitME

Measurement Error Modelling using MCEM

Wenhan Hwang

David Warton

logLik.refitME function

<dl><dt>object</dt>
<dd>: fitted model objects of class <code>refitME</code>.</dd>
<dt>...</dt>
<dd>: further arguments passed through to <code>lm</code> or <code>glm</code>.</dd></dl>

Arguments

Jakub Stoklosa, Wen-Han Hwang and David I. Warton.

Author

Extract log-Likelihoods for refitME model objects — logLik.refitME

<dl>

<dt>object</dt>
<dd>: fitted model objects of class <code>refitME</code>.</dd>


<dt>...</dt>
<dd>: further arguments passed through to <code>lm</code> or <code>glm</code>.</dd>

</dl>

logLik.refitME: Extract log-Likelihoods for `refitME` model objects

Description

Usage

Value

Arguments

Author

See Also