Author: Kimiko Osada BowmanPublisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 32
Book Description
Biases and Covariances of Maximum Likelihood Estimators
Author: Kimiko Osada BowmanPublisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 32
Book Description
Statistics of Directional Data
Author: K. V. MardiaPublisher: Academic Press
ISBN: 148321866X
Category : Mathematics
Languages : en
Pages : 380
Book Description
Probability and Mathematical Statistics: A Series of Monographs and Textbooks: Statistics of Directional Data aims to provide a systematic account of statistical theory and methodology for observations which are directions. The publication first elaborates on angular data and frequency distributions, descriptive measures, and basic concepts and theoretical models. Discussions focus on moments and measures of location and dispersion, distribution function, corrections for grouping, calculation of the mean direction and the circular variance, interrelations between different units of angular measurement, and diagrammatical representation. The book then examines fundamental theorems and distribution theory, point estimation, and tests for samples from von Mises populations. The text takes a look at non-parametric tests, distributions on spheres, and inference problems on the sphere. Topics include tests for axial data, point estimation, distribution theory, moments and limiting distributions, and tests of goodness of fit and tests of uniformity. The publication is a dependable reference for researchers interested in probability and mathematical statistics.
Adjusted Maximum Likelihood Estimation of the Moments of Lognormal Populations from Type 1 Censored Samples
Author: Timothy A. CohnPublisher:
ISBN:
Category : Lognormal distribution
Languages : en
Pages : 44
Book Description
An Introduction to Bartlett Correction and Bias Reduction
Author: Gauss M. CordeiroPublisher: Springer Science & Business Media
ISBN: 3642552552
Category : Mathematics
Languages : en
Pages : 113
Book Description
This book presents a concise introduction to Bartlett and Bartlett-type corrections of statistical tests and bias correction of point estimators. The underlying idea behind both groups of corrections is to obtain higher accuracy in small samples. While the main focus is on corrections that can be analytically derived, the authors also present alternative strategies for improving estimators and tests based on bootstrap, a data resampling technique and discuss concrete applications to several important statistical models.
Measurement Error Models
Author: Wayne A. FullerPublisher: John Wiley & Sons
ISBN: 0470317337
Category : Mathematics
Languages : en
Pages : 474
Book Description
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "The effort of Professor Fuller is commendable . . . [the book] provides a complete treatment of an important and frequently ignored topic. Those who work with measurement error models will find it valuable. It is the fundamental book on the subject, and statisticians will benefit from adding this book to their collection or to university or departmental libraries." -Biometrics "Given the large and diverse literature on measurement error/errors-in-variables problems, Fuller's book is most welcome. Anyone with an interest in the subject should certainly have this book." -Journal of the American Statistical Association "The author is to be commended for providing a complete presentation of a very important topic. Statisticians working with measurement error problems will benefit from adding this book to their collection." -Technometrics " . . . this book is a remarkable achievement and the product of impressive top-grade scholarly work." -Journal of Applied Econometrics Measurement Error Models offers coverage of estimation for situations where the model variables are observed subject to measurement error. Regression models are included with errors in the variables, latent variable models, and factor models. Results from several areas of application are discussed, including recent results for nonlinear models and for models with unequal variances. The estimation of true values for the fixed model, prediction of true values under the random model, model checks, and the analysis of residuals are addressed, and in addition, procedures are illustrated with data drawn from nearly twenty real data sets.
Maximum Likelihood Estimation in Small Samples
Author: L. R. ShentonPublisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 200
Book Description
Order Statistics and Their Use in Testing and Estimation: Estimates based on order statistics of samples from various populations
Author: Harman Leon HarterPublisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 832
Book Description
Nuclear Science Abstracts
Author: Partial Least Squares Regression
Author: R. Dennis CookPublisher: CRC Press
ISBN: 1040051324
Category : Mathematics
Languages : en
Pages : 448
Book Description
Partial least squares (PLS) regression is, at its historical core, a black-box algorithmic method for dimension reduction and prediction based on an underlying linear relationship between a possibly vector-valued response and a number of predictors. Through envelopes, much more has been learned about PLS regression, resulting in a mass of information that allows an envelope bridge that takes PLS regression from a black-box algorithm to a core statistical paradigm based on objective function optimization and, more generally, connects the applied sciences and statistics in the context of PLS. This book focuses on developing this bridge. It also covers uses of PLS outside of linear regression, including discriminant analysis, non-linear regression, generalized linear models and dimension reduction generally. Key Features: • Showcases the first serviceable method for studying high-dimensional regressions. • Provides necessary background on PLS and its origin. • R and Python programs are available for nearly all methods discussed in the book. This book can be used as a reference and as a course supplement at the Master's level in Statistics and beyond. It will be of interest to both statisticians and applied scientists.
Order Statistics & Inference
Author: Narayanaswamy BalakrishnanPublisher: Elsevier
ISBN: 1483297497
Category : Mathematics
Languages : en
Pages : 399
Book Description
The literature on order statistics and inferenc eis quite extensive and covers a large number of fields ,but most of it is dispersed throughout numerous publications. This volume is the consolidtion of the most important results and places an emphasis on estimation. Both theoretical and computational procedures are presented to meet the needs of researchers, professionals, and students. The methods of estimation discussed are well-illustrated with numerous practical examples from both the physical and life sciences, including sociology,psychology,a nd electrical and chemical engineering. A complete, comprehensive bibliography is included so the book can be used both aas a text and reference.