Verwandte Artikel zu Generalized Linear Mixed Models with Applications in...
- VerlagSpringer
- Erscheinungsdatum2023
- ISBN 10 3031327993
- ISBN 13 9783031327995
- EinbandTapa dura
- SpracheEnglisch
- Auflage1
- Anzahl der Seiten444
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
Verlag:
Springer International Publishing AG, 2023
ISBN 10: 3031327993
ISBN 13: 9783031327995
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Zustand: Brand New. Ships SAME or NEXT business day. We Ship to APO/FPO addr. Choose EXPEDITED shipping and receive in 2-5 business days within the United States. See our member profile for customer support contact info. We have an easy return policy. Bestandsnummer des Verkäufers 52498081
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
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Zustand: New. Bestandsnummer des Verkäufers 401128303
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
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Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Bestandsnummer des Verkäufers ABEJUNE24-14134
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
Verlag:
Springer International Publishing Aug 2023, 2023
ISBN 10: 3031327993
ISBN 13: 9783031327995
Neu
Hardcover
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access bookoffers an introduction to mixed generalized linear models with applications to the biological sciences, basically approached from an applications perspective, without neglecting the rigor of the theory. For this reason, the theory that supports each of the studied methods is addressed and later - through examples - its application is illustrated. In addition, some of the assumptions and shortcomings of linear statistical models in general are also discussed.An alternative to analyse non-normal distributed response variables is the use of generalized linear models (GLM) to describe the response data with an exponential family distribution that perfectly fits the real response. Extending this idea to models with random effects allows the use of Generalized Linear Mixed Models (GLMMs). The use of these complex models was not computationally feasible until the recent past, when computational advances and improvements to statistical analysis programs allowed users to easily, quickly, and accurately apply GLMM to data sets. GLMMs have attracted considerable attention in recent years. The word 'Generalized' refers to non-normal distributions for the response variable and the word 'Mixed' refers to random effects, in addition to the fixed effects typical of analysis of variance (or regression). With the development of modern statistical packages such as Statistical Analysis System (SAS), R, ASReml, among others, a wide variety of statistical analyzes are available to a wider audience. However, to be able to handle and master more sophisticated models requires proper training and great responsibility on the part of the practitioner to understand how these advanced tools work. GMLM is an analysis methodology used in agriculture and biology that can accommodate complex correlation structures and types of response variables. 444 pp. Englisch. Bestandsnummer des Verkäufers 9783031327995
Anzahl: 2 verfügbar
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
Verlag:
Springer International Publishing, 2023
ISBN 10: 3031327993
ISBN 13: 9783031327995
Neu
Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access bookoffers an introduction to mixed generalized linear models with applications to the biological sciences, basically approached from an applications perspective, without neglecting the rigor of the theory. For this reason, the theory that supports each of the studied methods is addressed and later - through examples - its application is illustrated. In addition, some of the assumptions and shortcomings of linear statistical models in general are also discussed.An alternative to analyse non-normal distributed response variables is the use of generalized linear models (GLM) to describe the response data with an exponential family distribution that perfectly fits the real response. Extending this idea to models with random effects allows the use of Generalized Linear Mixed Models (GLMMs). The use of these complex models was not computationally feasible until the recent past, when computational advances and improvements to statistical analysis programs allowed users to easily, quickly, and accurately apply GLMM to data sets. GLMMs have attracted considerable attention in recent years. The word 'Generalized' refers to non-normal distributions for the response variable and the word 'Mixed' refers to random effects, in addition to the fixed effects typical of analysis of variance (or regression). With the development of modern statistical packages such as Statistical Analysis System (SAS), R, ASReml, among others, a wide variety of statistical analyzes are available to a wider audience. However, to be able to handle and master more sophisticated models requires proper training and great responsibility on the part of the practitioner to understand how these advanced tools work. GMLM is an analysis methodology used in agriculture and biology that can accommodate complex correlation structures and types of response variables. Bestandsnummer des Verkäufers 9783031327995
Anzahl: 1 verfügbar