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Book Conditionally Specified Distributions

Download or read book Conditionally Specified Distributions written by Barry C. Arnold and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of conditional specification is not new. It is likely that earlier investigators in this area were deterred by computational difficulties encountered in the analysis of data following con ditionally specified models. Readily available computing power has swept away that roadblock. A broad spectrum of new flexible models may now be added to the researcher's tool box. This mono graph provides a preliminary guide to these models. Further development of inferential techniques, especially those involving concomitant variables, is clearly called for. We are grateful for invaluable assistance in the preparation of this monograph. In Riverside, Carole Arnold made needed changes in grammer and punctuation and Peggy Franklin miraculously transformed minute hieroglyphics into immaculate typescript. In Santander, Agustin Manrique ex pertly transformed rough sketches into clear diagrams. Finally, we thank the University of Cantabria for financial support which made possible Barry C. Arnold's enjoyable and productive visit to S- tander during the initial stages of the project. Barry C. Arnold Riverside, California USA Enrique Castillo Jose Maria Sarabia Santander, Cantabria Spain January, 1991 Contents 1 Conditional Specification 1 1.1 Why? ............. ........ . 1 1.2 How may one specify a bivariate distribution? 2 1.3 Early work on conditional specification 4 1.4 Organization of this monograph . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 5 2 Basic Theorems 7 Compatible conditionals: The finite discrete case.

Book Conditional Specification of Statistical Models

Download or read book Conditional Specification of Statistical Models written by Barry C. Arnold and published by Springer Science & Business Media. This book was released on 2007-06-02 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efforts to visualize multivariate densities necessarily involve the use of cross-sections, or, equivalently, conditional densities. This book focuses on distributions that are completely specified in terms of conditional densities. They are appropriately used in any modeling situation where conditional information is completely or partially available. All statistical researchers seeking more flexible models than those provided by classical models will find conditionally specified distributions of interest.

Book Flexible Imputation of Missing Data  Second Edition

Download or read book Flexible Imputation of Missing Data Second Edition written by Stef van Buuren and published by CRC Press. This book was released on 2018-07-17 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.

Book A Test for Comparing Multiple Misspecified Conditional Distributions

Download or read book A Test for Comparing Multiple Misspecified Conditional Distributions written by Norman R. Swanson and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper introduces a conditional Kolmogorov test, in the spirit of Andrews (1997), that allows for comparison of multiple misspecifed conditional distribution models, for the case of dependent observations. A conditional confidence interval version of the test is also discussed. Model accuracy is measured using a distributional analog of mean square error, in which the squared (approximation) error associated with a given model, say model i, is measured in terms of the average over U of E((Fi(u|Zt,0iĴ)-F0(u|Zt0o))squared), where U is a possibly unbounded set on the real line, Zt is the conditioning information set, Fi is the distribution function of a particular candidate model, and F0 is the true (unkown) distribution function. When comparing more than two models, a "benchmark" model is specified, and the test is constructed along the lines of the "reality check" of White (2000). Valid asymptotic critical values are obtained via a version of the block bootstrap which properly captures the effect of parameter estimation error. The results of a small Monte Carlo experiment indicate that the conditional confidence interval version of the test has reasonable finite sample properties even for samples with as few as 60 observations.

Book Limit Theorems for Conditional Distributions

Download or read book Limit Theorems for Conditional Distributions written by George Powell Steck and published by . This book was released on 1955 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Conditional Probability Distributions

Download or read book Conditional Probability Distributions written by Tue Tjur and published by . This book was released on 1974 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary in Danish.

Book Continuous Bivariate Distributions

Download or read book Continuous Bivariate Distributions written by N. Balakrishnan and published by Springer Science & Business Media. This book was released on 2009-05-31 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: Along with a review of general developments relating to bivariate distributions, this volume also covers copulas, a subject which has grown immensely in recent years. In addition, it examines conditionally specified distributions and skewed distributions.

Book Continuous Bivariate Distributions

Download or read book Continuous Bivariate Distributions written by N Balakrishnan and published by Springer. This book was released on 2009-06-22 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: Along with a review of general developments relating to bivariate distributions, this volume also covers copulas, a subject which has grown immensely in recent years. In addition, it examines conditionally specified distributions and skewed distributions.

Book On Conditional Distributions for Stochastic Processes

Download or read book On Conditional Distributions for Stochastic Processes written by Lester E. Dubins and published by . This book was released on 1972 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author asks THE FOLLOWING QUESTION: What meaning can and should be given to conditional probability or conditional distribution, given an event of probability zero. This important question is challenging and vexing, but no fully satisfactory answer is known. One difficulty with the conventional countably additive approach is that there exists no everywhere proper regular conditional distribution given the tail sigma-field, nor given the field of events in the past of a wide sense stopping time. It is suggested that this difficulty can sometimes, and perhaps always, be overcome, if finitely additive probability measures are accepted. (Author).

Book Parametric Distributional Flexibility and Conditional Variance Models with an Application to Hourly Exchange Rates

Download or read book Parametric Distributional Flexibility and Conditional Variance Models with an Application to Hourly Exchange Rates written by Ms.Jenny N. Lye and published by International Monetary Fund. This book was released on 1998-03-01 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper builds on the ARCH approach for modeling distributions with time-varying conditional variance by using the generalized Student t distribution. The distribution offers flexibility in modeling both leptokurtosis and asymmetry (characteristics seen in high-frequency financial time series data), nests the standard normal and Student t distributions, and is related to the Gram Charlier and mixture distributions. An empirical ARCH model based on this distribution is formulated and estimated using hourly exchange rate returns for four currencies. The generalized Student t is found to better model the empirical conditional and unconditional distributions than other distributional specifications.

Book Comparing Conditional Distributions Under Measurement Errors of Known Variances

Download or read book Comparing Conditional Distributions Under Measurement Errors of Known Variances written by Stanford University. Department of Statistics and published by . This book was released on 1968 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Distributions Characterized Through Conditional Expectations

Download or read book Distributions Characterized Through Conditional Expectations written by K. Balasubramanian and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using conditional expectations, we present results that lead to the characterization of several distributions. Both absolutely continuous random variables and discrete random variables are considered. In the case of absolutely continuous random variables, the results lead to the characterization of a family of distributions while in the case of discrete random variables, the distribution is almost uniquely determined under the stated conditions.

Book Sufficient Conditions for the Weak Convergence of Conditional Probability Distributions in a Metric Space

Download or read book Sufficient Conditions for the Weak Convergence of Conditional Probability Distributions in a Metric Space written by Bruce E. Trumbo and published by . This book was released on 1965 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Lectures on Probability Theory and Mathematical Statistics   3rd Edition

Download or read book Lectures on Probability Theory and Mathematical Statistics 3rd Edition written by Marco Taboga and published by Createspace Independent Publishing Platform. This book was released on 2017-12-08 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of 80 short and self-contained lectures covering most of the topics that are usually taught in intermediate courses in probability theory and mathematical statistics. There are hundreds of examples, solved exercises and detailed derivations of important results. The step-by-step approach makes the book easy to understand and ideal for self-study. One of the main aims of the book is to be a time saver: it contains several results and proofs, especially on probability distributions, that are hard to find in standard references and are scattered here and there in more specialistic books. The topics covered by the book are as follows. PART 1 - MATHEMATICAL TOOLS: set theory, permutations, combinations, partitions, sequences and limits, review of differentiation and integration rules, the Gamma and Beta functions. PART 2 - FUNDAMENTALS OF PROBABILITY: events, probability, independence, conditional probability, Bayes' rule, random variables and random vectors, expected value, variance, covariance, correlation, covariance matrix, conditional distributions and conditional expectation, independent variables, indicator functions. PART 3 - ADDITIONAL TOPICS IN PROBABILITY THEORY: probabilistic inequalities, construction of probability distributions, transformations of probability distributions, moments and cross-moments, moment generating functions, characteristic functions. PART 4 - PROBABILITY DISTRIBUTIONS: Bernoulli, binomial, Poisson, uniform, exponential, normal, Chi-square, Gamma, Student's t, F, multinomial, multivariate normal, multivariate Student's t, Wishart. PART 5 - MORE DETAILS ABOUT THE NORMAL DISTRIBUTION: linear combinations, quadratic forms, partitions. PART 6 - ASYMPTOTIC THEORY: sequences of random vectors and random variables, pointwise convergence, almost sure convergence, convergence in probability, mean-square convergence, convergence in distribution, relations between modes of convergence, Laws of Large Numbers, Central Limit Theorems, Continuous Mapping Theorem, Slutsky's Theorem. PART 7 - FUNDAMENTALS OF STATISTICS: statistical inference, point estimation, set estimation, hypothesis testing, statistical inferences about the mean, statistical inferences about the variance.

Book Skew Elliptical Distributions and Their Applications

Download or read book Skew Elliptical Distributions and Their Applications written by Marc G. Genton and published by CRC Press. This book was released on 2004-07-27 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state-of-the-art advances in skew-elliptical distributions and provides many new developments in a single volume, collecting theoretical results and applications previously scattered throughout the literature. The main goal of this research area is to develop flexible parametric classes of distributions beyond the classical no