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Titlebook: Vector Generalized Linear and Additive Models; With an Implementati Thomas W. Yee Textbook 2015 Thomas Yee 2015 Additive Model Theory.Gener

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楼主: JAZZ
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Categorical Data Analysisl logit model for nominal responses; and for ordinal responses: the proportional and non-proportional-odds models, continuation and stopping ratio models, and the adjacent categories model. Some other topics includes the . argument for allowing ..-specific covariates, the Poisson trick, marginal eff
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Zero-Inflated, Zero-Altered and Positive Discrete Distributionsflated distributions are also mentioned. Specific examples include the zero-inflated Poisson and positive-binomial distributions. Another example concerns closed-population capture–recapture estimation, which is described in relatively more detail as an application of a positive-Bernoulli distributi
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Textbook 2015 Comprising of about half-a-dozen major classes of statistical models, and fortified with necessary infrastructure to make the models more fully operable, the framework allows analyses based on many semi-traditional applied statistics models to be performed as a coherent whole..Since their advent in
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Reduced-Rank VGLMsthod, e.g., when applied to the multinomial logit model it leads to the stereotype model. Another related class of models is row–column interaction models (RCIMs), and two-parameter RR-VGLMs are described in this chapter. Some applications mentioned here and/or developed elsewhere include quasi-variances and indirect gradient analysis.
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Constrained Quadratic Ordinatione the basic ideas of ordination, the species packing model, latent variables as gradients, CQO estimation and interpretation, biplots, and calibration. Unconstrained QO (indirect gradient analysis) is also described. Some real-data examples are given.
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Constrained Additive Ordination’ response curves as a function of the dominant gradient—e.g., they are not constrained to be symmetric bell-shaped, as with QRR-VGLMs. A few practical suggestions are given to aid the use of the modelling function ..
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