| 1. | (for further discussion see section on Fisher information matrix ).
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| 2. | Is the observed information matrix at \ theta _ 0.
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| 3. | Considered purely as a matrix, it is known as the Fisher information matrix.
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| 4. | The inverse matrix of the variance-matrix is called the " information matrix ".
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| 5. | Fisher's information matrix for the four parameter case is singularities at the following values:
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| 6. | Aryal and Nadarajah calculated Fisher's information matrix for the four parameter case as follows:
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| 7. | These logarithmic variances and covariance are the elements of the Fisher information matrix for the beta distribution.
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| 8. | The Fisher information matrix for estimating the parameters of a multivariate normal distribution has a closed form expression.
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| 9. | The Fisher-information matrix is used to calculate the covariance matrices associated with maximum-likelihood estimates.
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| 10. | Therefore, the Fisher information matrix has 6 independent off-diagonal + 4 diagonal = 10 independent components.
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