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Introductory Statistical Inference with the Likelihood Function

throughout the book. There is also coverage of severity and finite population sampling. The material was developed from an introductory statistical;

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Likelihood & Bayesian Inference

discusses the importance of statistical models in applied quantitative research and the central role of the likelihood function, describing;

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Likelihood and Bayesian Inference

discusses the importance of statistical models in applied quantitative research and the central role of the likelihood function, describing;

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Constrained Statistical Inference

sociology and econometrics to biostatistics. This volume enables professionals in these and related fields to master the concepts of statistical;

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Mathematical Statistics

likelihood function. It also emphasizes the important ideas in statistical modeling, such as sufficiency, exponential family distributions, and large;

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Mathematical Foundations of Infinite-Dimensional Statistical Models

In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood;

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Semimartingales and their Statistical Inference

Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its;

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Semimartingales and Their Statistical Inference

Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its;

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Likelihood

the subject. Edwards argues that the appropriate axiomatic basis for inductive inference is not that of probability, with its addition axiom;

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Statistical Inference Based on the likelihood

The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods. This book;

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Statistical Inference Based On The Likelihood

The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods. This book;

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Machine Interval Experiments

extended experiment allows a statistical decision made with the aid of a computer to be equivalent to a numerical proof. From the integrative;

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Maximum Likelihood Estimation and Inference

free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates;

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Modes Of Parametric Statistical Inference

of statistics and the principles underlying statistical inference, including students in mathematics and the philosophy of science. Readers with a;

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Statistical Inference

methods for hypothesis testing. After an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood;

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Statistical Inference

methods for hypothesis testing. After an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood;

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Confidence Intervals in Generalized Regression Models

ratio tests. Uses Statistical Inference Package to Make Inferences on Real-Valued Parameter Functions Offering software that helps with;

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Confidence Intervals in Generalized Regression Models

ratio tests. Uses Statistical Inference Package to Make Inferences on Real-Valued Parameter Functions Offering software that helps with;

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Statistical Inference in Stochastic Processes

statistical techniques in image analysis and processing, develops likelihood methods for inference about parameters that determine the drift and the;

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Probability and Statistical Inference

Priced very competitively compared with other textbooks at this level! This gracefully organized textbook reveals the rigorous theory;

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Probability and Statistical Inference

Priced very competitively compared with other textbooks at this level! This gracefully organized textbook reveals the rigorous theory;

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Aspects of Statistical Inference

is ultimately about the concepts themselves. Written with clarity and depth, Aspects of Statistical Inference: Provides a theoretical and historical;

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Introduction to Bayesian Statistics

with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: * Topics including the Joint Likelihood function and;

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Econometric Modeling

, with estimation and inference based on the likelihood function. Substantive issues are always addressed, showing how both statistical and;

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Statistical Inference Based on Divergence Measures

their properties. The author then examines the statistical analysis of discrete multivariate data with emphasis is on problems in contingency;

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Statistical Inference Based on Divergence Measures

their properties. The author then examines the statistical analysis of discrete multivariate data with emphasis is on problems in contingency;

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Statistical Inference

absolutely continuous distributions and random sample which are the basic concepts on which Statistical Inference is built up, with examples that;

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