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Generalized linear modelling for parasitologists
Parasitology Today, 1997Typically, the distribution of macroparasites over their host population is highly aggregated and empirically best described by the negative binomial distribution. For parasitologists, this poses a statistical provlem, which is often tackled by log-transforming the parasite data prior to analysis by parametric tests. Here, Ken Wilson and Bryan Grenfell
Wilson, Kenneth, Grenfell, Bryan T.
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Model Checks for Generalized Linear Models
Scandinavian Journal of Statistics, 2002In this paper we propose and study non‐parametric tests for the validity of (composite) Generalized Linear Models with a given parametric link structure, which are based on certain empirical processes marked by the residuals. When properly transformed to their innovation part the resulting test statistics are distribution‐free.
Stute, Winfried, Zhu, Li-Xing
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American Journal of Orthodontics and Dentofacial Orthopedics, 2023
Tomasz Burzykowski +3 more
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Tomasz Burzykowski +3 more
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1978
In the two preceding chapters we have set forth, in some detail, the estimation of parameters and the properties of the resulting estimators in the context of the standard GLM. We recall that rather stringent assumptions were made relative to the error process and the explanatory variables.
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In the two preceding chapters we have set forth, in some detail, the estimation of parameters and the properties of the resulting estimators in the context of the standard GLM. We recall that rather stringent assumptions were made relative to the error process and the explanatory variables.
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A nonparametric general linear model
Computers and Biomedical Research, 1972Abstract A matrix formulation of the Kruskal-Wallis analysis of variance is presented. This formulation illustrates the parallel nature of the parametric general linear model and the Kruskal-Wallis model. Using the matrix formulation, it is shown that the Kruskal-Wallis method can be implemented on a digital computer as a special case of a general ...
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An Introduction to Generalized Linear Models
Technometrics, 2002(2002). An Introduction to Generalized Linear Models. Technometrics: Vol. 44, No. 4, pp. 406-407.
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Introducing the generalized linear model: general linear model
2019This chapter reviews the generalized linear model (GLZM), which is an extremely useful and increasingly popular framework approach to analysing data. Since it relies on making assumptions about the distribution of data, it is parametric. In particular, the chapter looks at the general linear model (GLM), a sub-framework of the generalized linear model ...
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A linear generalization of Stackelberg’s model
Theory and Decision, 2008We study an extension of Stackelberg's model in which many firms can produce at many different times. Demand is affine while cost is linear. In this setting, we investigate whether Stackelberg's results in a two-firm game are robust when the number of firms increases.
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2023
General Linear Model methods are the most widely used in data analysis in applied empirical research. Still, there exists no compact text that can be used in statistics courses and as a guide in data analysis. This volume fills this void by introducing the General Linear Model (GLM), whose basic concept is that an observed variable can be explained ...
Alexander von Eye, Wolfgang Wiedermann
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General Linear Model methods are the most widely used in data analysis in applied empirical research. Still, there exists no compact text that can be used in statistics courses and as a guide in data analysis. This volume fills this void by introducing the General Linear Model (GLM), whose basic concept is that an observed variable can be explained ...
Alexander von Eye, Wolfgang Wiedermann
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Linear and Generalized Linear Mixed Models and Their Applications
Technometrics, 2008(2008). Linear and Generalized Linear Mixed Models and Their Applications. Technometrics: Vol. 50, No. 1, pp. 93-94.
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