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Since the introduction of the idea of generalized linear models (GLM) in early seventies, during the past four decades the modelling of statistical data have... Læs mere
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This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R.
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This Element introduces the basics of Bayesian regression modeling using modern computational tools and assumes that the reader has taken a... Læs mere
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This Element introduces the basics of Bayesian regression modeling using modern computational tools and assumes that the reader has taken a... Læs mere
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It returns to Poisson events to discuss another unexpected result, followed by the use of spatial Poisson events in... Læs mere
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This book examines statistical models for frequency data. After developing a sound applied and theoretical basis for frequency models analogous to ANOVA and... Læs mere
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This book offers a comprehensive reference guide to neutrosophic theory and its applications in decision-making in numerous disciplines, ranging from business, economics and management, computer science, health and environmental sciences, and many others.
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Instead, we present the following conclusion as an example: (1) The average duration of hospital stays for Group A is at least half a day shorter than for Group B. (3) Group A has an average hospital stay that is, on average, no more than 94% of that of Group B.
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This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking.
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Sufficient conditions should be presented, such as “the average number of days until recovery in patients who take new drugs is sufficiently short compared to the control group, evaluated from a medical point of view”, without paying attention to necessary conditions.
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This book presents recent advances of Bayesian inference in structured tensor decompositions.
Bemærk: Kan ikke leveres før jul.
This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking.