Expected Information Matrix
The Expected Information Matrix is a theoretical construct in statistical inference that belongs to the class of information matrices and is specifically defined as the expected value of the second derivative (or Hessian) of the log-likelihood function with respect to the model parameters, serving to quantify the amount of information an observable random variable carries about the unknown parameters.
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Fisher Information Matrix
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The Covariance Matrix of the Information Matrix Test
Tony Lancaster · Econometrica · 1984 · 119 citations
Education, Educational Assessment, Educational Measurement +8
Andrew Chesher · Economics Letters · 1983 · 104 citations
Natural Sciences, Educational Assessment, Information Theory +4
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University of Amsterdam
Amsterdam, The Netherlands
6 h-index
9 publications
194 citations
Universidade de São Paulo
São Paulo, Brazil
5 h-index
6 publications
197 citations

Universidade Federal de Pernambuco
Recife, Brazil
4 h-index
5 publications
117 citations
University of Kent
Canterbury, United Kingdom
3 h-index
6 publications
225 citations
Universidade Federal Rural de Pernambuco
Recife, Brazil
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3 publications
109 citations
University of South Carolina
Columbia, United States
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4 publications
546 citations
University College London
London, United Kingdom
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5 publications
222 citations

University of British Columbia
Vancouver, Canada
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2 publications
158 citations
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SEM · 3 publications · 502 citations
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