Daryl Pregibon. Resistant fits for some commonly used logistic models with medical applications. Biometrics, 38:485--498, 1982. Home/Search Document Not in Database Summary Related Articles Check |
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Statistical Methods For The Analysis Of A.. - Frome, Smith.. (1994) (Correct)
....when the dependent variable is in the regular exponential family. McCullagh [15] extended this result to quasi likelihood estimation which requires specification of the mean and variance function. Extension of the IWLS method to resistant robust regression has been described by [9] and [20], and the computational approach described in [6] see chapter 6) is used here. Similar resistant regression methods have been applied to the analysis of drug concentration time data encountered in human bioavailability studies [8] To describe this approach, consider the following weighted sum of ....
....where u = y jk Gamma y jk ) OEy jk is the standardized residual using the current estimates of fi and OE. This is known as an M estimator with Huber s loss function. The tuning constant , k, must be specified and we use k = 1:345 which leads to estimates with approximately 95 efficiency [20]. Therefore, we obtain resistant quasi likelihood estimates by adjusting the weights in the diagonal matrix W in Equation (4) by multiplying in the Huber weight in (5) see Appendix D for details) Following the last iteration, the coefficient of variation is estimated using a scaled MAD estimate ....
Daryl Pregibon. Resistant fits for some commonly used logistic models with medical applications. Biometrics, 38:485--498, 1982.
Statistical Methods for the Blood Beryllium.. - Frome, Smith.. (1996) (Correct)
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Daryl Pregibon. Resistant fits for some commonly used logistic models with medical applications. Biometrics, 38:485--498, 1982.
On the Misuses of Artificial Neural Networks for.. - Schwarzer, Vach.. (2000) (1 citation) (Correct)
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Pregibon D. Resistant fits for some commonly used logistic models with medical applications. Biometrics. 1982;38:485-98.
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