Author: Andrew L. RukhinPublisher:
ISBN:
Category :
Languages : en
Pages : 15
Book Description
Improved Estimation in Lognormal Models
Author: Andrew L. RukhinImproved Estimation in Lognormal Regression Models
Author: Andrew L. RukhinPrediction and Improved Estimation in Linear Models
Author: John BibbyLognormal Distributions
Author: CrowPublisher: Routledge
ISBN: 1351434683
Category : Mathematics
Languages : en
Pages : 412
Book Description
Presenting the first comprehensive review of the subject's theory and applications inmore than 15 years, this outstanding reference encompasses the most-up-to-date advancesin lognormal distributions in thorough, detailed contributions by specialists in statistics,business and economics , industry, biology , ecology, geology, and meteorology.Lognormal Distributions describes the theory and methods of point and intervalestimation as well as the testing of hypotheses clearly and precisely from a modemviewpoint-not only for the basic two-parameter lognormal distribution but also for itsgeneralizations, including three parameters, truncated distributions, delta-lognormaldistributions, and two or more dimensions.Featuring over 600 references plus author and subject indexes, this volume rev iews thesubject's history .. . gives explicit formulas for minimum variance unbiased estimates ofparameters and their variances ... provides optimal tests of hypotheses and confidenceinterval procedures for various functions of the parameters in the two-parameter model. .. and discusses practical methods of analysis for truncated, censored, or groupedsamples.
Parameter Estimation in Reliability and Life Span Models
Author: A Clifford CohenPublisher: CRC Press
ISBN: 1000147231
Category : Mathematics
Languages : en
Pages : 312
Book Description
Offers an applications-oriented treatment of parameter estimation from both complete and censored samples; contains notations, simplified formats for estimates, graphical techniques, and numerous tables and charts allowing users to calculate estimates and analyze sample data quickly and easily. Anno
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
Improved Estimation for Linear Models Under Different Loss Functions
Author: Zahirul HoquePublisher:
ISBN:
Category : Linear models (Statistics)
Languages : en
Pages : 344
Book Description
This thesis investigates improved estimators of the parameters of the linear regression models with normal errors, under sample and non-sample prior information about the value of the parameters. The estimators considered are the unrestricted estimator (UE), restricted estimator (RE), shrinkage preliminary test estimator (SPTE), and shrinkage estimator (SE). The performance of the estimators are investigated with respect to bias, squared error and linex loss. For the analyses of the risk functions of the estimators, analytical, graphical and numerical procedures are adopted.
Theory of Point Estimation
Author: Erich L. LehmannPublisher: Springer Science & Business Media
ISBN: 0387227288
Category : Mathematics
Languages : en
Pages : 610
Book Description
This second, much enlarged edition by Lehmann and Casella of Lehmann's classic text on point estimation maintains the outlook and general style of the first edition. All of the topics are updated, while an entirely new chapter on Bayesian and hierarchical Bayesian approaches is provided, and there is much new material on simultaneous estimation. Each chapter concludes with a Notes section which contains suggestions for further study. This is a companion volume to the second edition of Lehmann's "Testing Statistical Hypotheses".
IMPROVED PARAMETER ESTIMATION OF THE LOG-LOGISTIC DISTRIBUTION WITH APPLICATIONS
Author: Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Abstract : In this report, we work with parameter estimation of the log-logistic distribution. We first consider one of the most common methods encountered in the literature, the maximum likelihood (ML) method. However, it is widely known that the maximum likelihood estimators (MLEs) are usually biased with a finite sample size. This motivates a study of obtaining unbiased or nearly unbiased estimators for this distribution. Specifically, we consider a certain `corrective' approach and Efron's bootstrap resampling method, which both can reduce the biases of the MLEs to the second order of magnitude. As a comparison, we also consider the generalized moments (GM) method. Monte Carlo simulation studies are conducted to compare the performances of the various estimators under consideration. Finally, two real-data examples are analyzed to illustrate the potential usefulness of the proposed estimators, especially when the sample size is small or moderate.
Erosion and Sediment Transport Measurement in Rivers
Author: Jim BogenPublisher:
ISBN: 9781901502428
Category : Science
Languages : en
Pages : 252
Book Description