Biased Estimators For The Parameters Of Linear Regression Model

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Biased Estimators for the Parameters of Linear Regression Model

Author : Bushra Abdalrasool Ali
Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783659388736
Total Pages : 96 pages
Book Rating : 4.3/5 (887 download)

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Book Synopsis Biased Estimators for the Parameters of Linear Regression Model by : Bushra Abdalrasool Ali

Download or read book Biased Estimators for the Parameters of Linear Regression Model written by Bushra Abdalrasool Ali and published by LAP Lambert Academic Publishing. This book was released on 2013 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work deal with biased estimation methods for estimating the parameters of general linear regression model when the data are ill-conditioned. We focus our attention on ordinary and generalized ridge regression estimators, Jackknife ridge estimators and principal components estimators. In chapter one introduction and historical review In chapter two basic concepts, definitions on linear regression model are presented. Moreover, the statistical properties of the ordinary least squares estimators are presented. Classes of biased estimators are discussed in chapter three when the data suffer from the multicollinearity problem. The procedures discussed in the preceding chapters were applied in chapter four to perform the regression analysis employing the data obtained from Midland Refineries Company in Iraq, for 12 years period in order to determine the effect of six different factors on the productivity of labor. The statistical programs, SPSS, and Minitab were employed to perform the required calculations.

Biased Estimators in the Linear Regression Model

Author : Götz Trenkler
Publisher :
ISBN 13 : 9783445020246
Total Pages : 163 pages
Book Rating : 4.0/5 (22 download)

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Book Synopsis Biased Estimators in the Linear Regression Model by : Götz Trenkler

Download or read book Biased Estimators in the Linear Regression Model written by Götz Trenkler and published by . This book was released on 1981 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Two Biased Estimation Techniques in Linear Regression: Application to Aircraft

Author :
Publisher :
ISBN 13 :
Total Pages : 44 pages
Book Rating : 4.:/5 (317 download)

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Book Synopsis Two Biased Estimation Techniques in Linear Regression: Application to Aircraft by :

Download or read book Two Biased Estimation Techniques in Linear Regression: Application to Aircraft written by and published by . This book was released on 1988 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Asymptotic Distribution of the Bias Corrected Least Squares Estimators in Measurement Error Linear Regression Models Under Long Memory

Download Asymptotic Distribution of the Bias Corrected Least Squares Estimators in Measurement Error Linear Regression Models Under Long Memory PDF Online Free

Author : Hira Koul
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Asymptotic Distribution of the Bias Corrected Least Squares Estimators in Measurement Error Linear Regression Models Under Long Memory by : Hira Koul

Download or read book Asymptotic Distribution of the Bias Corrected Least Squares Estimators in Measurement Error Linear Regression Models Under Long Memory written by Hira Koul and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article derives the consistency and asymptotic distribution of the bias corrected least squares estimators (LSEs) of the regression parameters in linear regression models when covariates have measurement error (ME) and errors and covariates form mutually independent long memory moving average processes. In the structural ME linear regression model, the nature of the asymptotic distribution of suitably standardized bias corrected LSEs depends on the range of the values of where ,, and are the LM parameters of the covariate, ME and regression error processes respectively. This limiting distribution is Gaussian when and non-Gaussian in the case . In the former case some consistent estimators of the asymptotic variances of these estimators and a log()-consistent estimator of an underlying LM parameter are also provided. They are useful in the construction of the large sample confidence intervals for regression parameters. The article also discusses the asymptotic distribution of these estimators in some functional ME linear regression models, where the unobservable covariate is non-random. In these models, the limiting distribution of the bias corrected LSEs is always a Gaussian distribution determined by the range of the values of )-)

On the Biased Estimation in Regression

Author : Esko Leskinen
Publisher :
ISBN 13 :
Total Pages : 166 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis On the Biased Estimation in Regression by : Esko Leskinen

Download or read book On the Biased Estimation in Regression written by Esko Leskinen and published by . This book was released on 1980 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Linear Regression Model

Author : J. G. M. Delissen
Publisher :
ISBN 13 : 9789061442035
Total Pages : 82 pages
Book Rating : 4.4/5 (42 download)

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Book Synopsis The Linear Regression Model by : J. G. M. Delissen

Download or read book The Linear Regression Model written by J. G. M. Delissen and published by . This book was released on 1988 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Simulation Comparing Biased Estimators in Linear Regression

Author : Michael John Lynn
Publisher :
ISBN 13 :
Total Pages : 102 pages
Book Rating : 4.:/5 (398 download)

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Book Synopsis A Simulation Comparing Biased Estimators in Linear Regression by : Michael John Lynn

Download or read book A Simulation Comparing Biased Estimators in Linear Regression written by Michael John Lynn and published by . This book was released on 1976 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Study on the Comparison of the Effectiveness of the Jackknife Method in the Biased Estimators

Author : Nilg√on Yildiz
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

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Book Synopsis A Study on the Comparison of the Effectiveness of the Jackknife Method in the Biased Estimators by : Nilg√on Yildiz

Download or read book A Study on the Comparison of the Effectiveness of the Jackknife Method in the Biased Estimators written by Nilg√on Yildiz and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this study, we proposed an alternative biased estimator. The linear regression model might lead to ill-conditioned design matrices because of the multicollinearity and thus result in inadequacy of the ordinary least squares estimator (OLS). Scientists have developed alternative estimation techniques that would eradicate the instability in the estimates. Several biased estimators such as Stein estimator, the ordinary ridge regression (ORR) estimator, the principal components regression (PCR) estimator. Liu developed a Liu estimator (LE) by combining the Stein estimator with the ORR estimator. Since both ORR and LE depend on OLS estimator, multicollinearity affects them both. Therefore, the ORR and LE may give misleading information in the presence of multicollinearity. To overcome this problem, Liu introduced a new estimator, which is based on k and d biasing parameters, the authors worked on developing an estimator that would still have the valuable characteristics of the Liu-type estimator (LTE) but have a smaller bias. We are proposing a modified jackknife Liu-type estimator (MJLTE) that was created by combining the ideas underlying both the LTE and JLTE. Under mean square error matrix criteria, the MJLTE is superior to Liu-type estimator (LTE) and jackknifed Liu-type estimator (JLTE). Finally, a real data example and a Monte Carlo simulation are also given to illustrate theoretical results.

Lectures on Probability Theory and Mathematical Statistics - 3rd Edition

Author : Marco Taboga
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781981369195
Total Pages : 670 pages
Book Rating : 4.3/5 (691 download)

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Book Synopsis Lectures on Probability Theory and Mathematical Statistics - 3rd Edition by : Marco Taboga

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.

Introduction to Linear Regression Analysis

Author : Douglas C. Montgomery
Publisher : John Wiley & Sons
ISBN 13 : 1119180171
Total Pages : 679 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Introduction to Linear Regression Analysis by : Douglas C. Montgomery

Download or read book Introduction to Linear Regression Analysis written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2015-06-29 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Fourth Edition "As with previous editions, the authors have produced a leading textbook on regression." —Journal of the American Statistical Association A comprehensive and up-to-date introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The Fifth Edition features numerous newly added topics, including: A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models Regression models with random effects in addition to a discussion on subsampling and the importance of the mixed model Tests on individual regression coefficients and subsets of coefficients Examples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data. In addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material. Introduction to Linear Regression Analysis, Fifth Edition is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.

Multicollinearity and Biased Estimation

Author : Josef Gruber
Publisher : Vandehoeck & Rupprecht
ISBN 13 :
Total Pages : 156 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Multicollinearity and Biased Estimation by : Josef Gruber

Download or read book Multicollinearity and Biased Estimation written by Josef Gruber and published by Vandehoeck & Rupprecht. This book was released on 1984 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:

NASA Technical Note

Author :
Publisher :
ISBN 13 :
Total Pages : 928 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis NASA Technical Note by :

Download or read book NASA Technical Note written by and published by . This book was released on 1975 with total page 928 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Theory of Ridge Regression Estimation with Applications

Author : A. K. Md. Ehsanes Saleh
Publisher : John Wiley & Sons
ISBN 13 : 1118644506
Total Pages : 404 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Theory of Ridge Regression Estimation with Applications by : A. K. Md. Ehsanes Saleh

Download or read book Theory of Ridge Regression Estimation with Applications written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2019-01-08 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications Theory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis. Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators. The authors also include problem sets to enhance learning. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource: Offers theoretical coverage and computer-intensive applications of the procedures presented Contains solutions and alternate methods for prediction accuracy and selecting model procedures Presents the first book to focus on ridge regression and unifies past research with current methodology Uses R throughout the text and includes a companion website containing convenient data sets Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.

Biased Estimation in Linear Regression

Author : Katherine Cameron Spoonts
Publisher :
ISBN 13 :
Total Pages : 66 pages
Book Rating : 4.:/5 (83 download)

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Book Synopsis Biased Estimation in Linear Regression by : Katherine Cameron Spoonts

Download or read book Biased Estimation in Linear Regression written by Katherine Cameron Spoonts and published by . This book was released on 1974 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Linear Models and Generalizations

Author : C. Radhakrishna Rao
Publisher : Springer Science & Business Media
ISBN 13 : 3540742271
Total Pages : 583 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Linear Models and Generalizations by : C. Radhakrishna Rao

Download or read book Linear Models and Generalizations written by C. Radhakrishna Rao and published by Springer Science & Business Media. This book was released on 2007-10-15 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Revised and updated with the latest results, this Third Edition explores the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions. They not only use least squares theory, but also alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights of coverage include sensitivity analysis and model selection, an analysis of incomplete data, an analysis of categorical data based on a unified presentation of generalized linear models, and an extensive appendix on matrix theory.

Best Linear Unbiased and Invariant Estimators for Regression Parameters Based on Ordered Observations

Author : Z. Govindarajulu
Publisher :
ISBN 13 :
Total Pages : 20 pages
Book Rating : 4.:/5 (227 download)

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Book Synopsis Best Linear Unbiased and Invariant Estimators for Regression Parameters Based on Ordered Observations by : Z. Govindarajulu

Download or read book Best Linear Unbiased and Invariant Estimators for Regression Parameters Based on Ordered Observations written by Z. Govindarajulu and published by . This book was released on 1974 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: The best linear unbiased estimators of the parameters in the multiple regression model are obtained when the samples are arbitrarily censored. The homogeneity of variance, polynomial regression and simple linear regression become special cases of the above model. The formulas take simpler forms when the underlying distribution is symmetric and the subsamples are of equal size and are symmetrically censored. Best constant-risk estimators of the parameters alpha, beta, and sigma in the simple linear regression model are obtained. These results are applied to symmetric uniform and negative exponential cases. (Author).

V Hotine-Marussi Symposium on Mathematical Geodesy

Author : Fernando Sansò
Publisher : Springer Science & Business Media
ISBN 13 : 366210735X
Total Pages : 356 pages
Book Rating : 4.6/5 (621 download)

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Book Synopsis V Hotine-Marussi Symposium on Mathematical Geodesy by : Fernando Sansò

Download or read book V Hotine-Marussi Symposium on Mathematical Geodesy written by Fernando Sansò and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Just as in the era of great achievements by scientists such as Newton and Gauss, the mathematical theory of geodesy is continuing the tradition of producing exciting theoretical results, but today the advances are due to the great technological push in the era of satellites for earth observations and large computers for calculations. Every four years a symposium on methodological matters documents this ongoing development in many related underlying areas such as estimation theory, stochastic modelling, inverse problems, and satellite-positioning global-reference systems. This book presents developments in geodesy and related sciences, including applied mathematics, among which are many new results of high intellectual value to help readers stay on top of the latest happenings in the field.