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This function fits a wide range of generalized linear models using the iteratively reweighted least squares algorithm. The intended benefit of this function is for teaching. Its scope is similar to that of R's glm function, which should be preferred for operational use.
● Data Source:
CranContrib
● Keywords: ~models
● Alias: irls
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P__disp
(Package: msme) :
A function to calculate Pearson Chi2 and its dispersion statistic following glm and glm.nb.
This function calculates Pearson Chi2 statistic and the Pearson-based dipersion statistic. Values of the dispersion greater than 1 indicate model overdispersion. Values under 1 indicate under-dispersion.
● Data Source:
CranContrib
● Keywords:
● Alias: P__disp
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This function fits generalized linear models by maximizing the joint log-likeliood, which is set in a separate function. Null models are omitted from the fit. The post-estimation output is designed to work with existing reporting functions.
● Data Source:
CranContrib
● Keywords: ~models
● Alias: ml_glm3
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plot.ml_g_fit
(Package: msme) :
A plot method for objects of class ml_g_fit.
This function provides a four-way plot for fitted models.
● Data Source:
CranContrib
● Keywords: htest, models
● Alias: plot.ml_g_fit
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This function provides a compact summary for fitted models.
● Data Source:
CranContrib
● Keywords: ~models
● Alias: summary.msme
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This function demonstrates the use of maximum likelihood to fit ordinary least-squares regression models, by maximizing the likelihood as a function of the parameters. Only conditional normal errors are supported.
● Data Source:
CranContrib
● Keywords: ~models
● Alias: ml_g
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This function computes the asymptotic likelihood ratio test of two models by comparing twice the different in the log-likelihoods of the models with the Chi-squared distribution with degrees of freedom equal to the difference in the degrees of freedom of the models.
● Data Source:
CranContrib
● Keywords: ~models
● Alias: alrt
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This function fits generalized linear models by maximizing the joint log-likeliood, which is set in a separate function. Two-parameter members of the negative binomial family are covered. The post-estimation output is designed to work with existing reporting functions.
● Data Source:
CranContrib
● Keywords: ~models
● Alias: nbinomial
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This function provides a compact summary for fitted models.
● Data Source:
CranContrib
● Keywords: ~models
● Alias: summary.ml_g_fit
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This function uses QR decomposition to determine the hat matrix of a model given its design matrix X. It is specific to objects of class msme.
● Data Source:
CranContrib
● Keywords: ~models
● Alias: hatvalues.msme
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