Progress in Applied Statistics Research

Name: Progress in Applied Statistics Research
Brand: Nova Science Publishers Inc
Price: 241.99 EUR
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Ahsanullah Mohammad(Editor)

Nova Science Publishers Inc

Published on 7. August 2009

277 pages

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978-1-61728-664-3 (ISBN)

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Intro
PROGRESS IN APPLIED STATISTICSRESEARCH
PROGRESS IN APPLIED STATISTICSRESEARCH
CONTENTS
PREFACE
Chapter 1AN APPROXIMATE FAST BAYESIAN ALGORITHMFOR THE ANALYSIS AND FORECASTING OF THELOGNORMAL TIME SERIES
Abstract
1. Introduction
2. The Standard Dynamic Linear Models
The observation equation
The state equation
3. Dynamic Generalized Linear Models
4. Conditional Independence Structure
5. Lognormal Dynamic Models
6. Validation
7. Conclusion
References
Chapter 2EFFICIENT UNIFORM DESIGNS FOR MIXTUREEXPERIMENTS IN THREE AND FOUR COMPONENTS*
Abstract
1 Introduction
2 Uniform Designs and Uniformity Measures
3 Projection Designs
4 Optimality Criteria
5 Unconstrained Mixture Experiments
6 Constrained Mixture Experiments
Acknowledgments
Appendix A
References
Chapter 3DESIGN OF ACCELERATED LIFE TESTS FORPERIODIC INSPECTION WITH BURR TYPE IIIDISTRIBUTIONS: MODELS, ASSUMPTIONS ANDAPPLICATIONS
Abstract
1. Introduction
2. The Model and Test Method
Assumptions
Test Method
Standardization
3. Maximum Likelihood Estimation
4. Optimal Test Plans
Sensitivity Analysis
Sample Size Determination
5. Computational Results and Comparative Study
6. Test Procedure with Example
Example
7. Conclusion
References
Chapter 4PARAMETER ESTIMATION USING CRESSIE-READDIVERGENCE MEASURES WITH EXPONENTIALGROUPED CENSORED DATA*
Abstract
1 Introduction
2 Computational Results
3 Findings and Conclusions
References
Chapter 5ESTIMATING THE VARIANCE COMPONENTSOF ACCELERATED DEGRADATION MODELS*
Abstract
1 Introduction
2 Model and Estimating the Fixed Effect Parameters
3 Estimating the Variance Components
4 Simulation Study
5 Results and Conclusions
6 Application
References
Chapter 6ON THE RATIO OF THE SYMMETRIC DIFFERENCESOF ORDER STATISTICS
Abstract
1. Introduction
2. Main Result
References
Chapter 7MEASURING THE SURFACE ROUGHNESS USINGTHE SPATIAL STATISTICS APPLICATION
Abstract
1. Introduction and Notation
2. Spatial Statistics Analysis
3. Data Analysis
4. Conclusion
References
Chapter 8DIALLEL CROSSES WITH BLOCK SIZES THREE
Abstract
1. Introduction
2. Method of Construction
3. Analysis
4. Complete Diallel Crosses Plan with Unequal Number of Lines
4.1. Method of Construction
4.2. Analysis
5. Partial Diallel Crosses
6. Conclusion
Acknowledgements
Appendix: Tables
References
Chapter 9ON CHARACTERIZING DISTRIBUTIONS BYCONDITIONAL EXPECTATIONS OF FUNCTIONS OFGENERALIZED ORDER STATISTICS
Abstract
1. Introduction
2. Main Results
2.1. Applications
3. Characterizations by Reverse Ordering
3.1. Applications
Acknowledgments
References
Chapter 10ESTIMATING THE LOCATION AND SCALEPARAMETERS USING RANKED SET SAMPLING
Abstract
1. Introduction
2. Estimation Based on a RSS and a MRSS
3. Location Family
Scale Family
5. Location-Scale Family
6. Calculations
7. Application
8. Conclusion
References
Chapter 11ROBUST ESTIMATION IN CALIBRATIONMODELSUSING THE STUDENT-t DISTRIBUTION
Abstract
1. Introduction
2. The Calibration Model without Measurement Error
2.1. A Simulation Study
2.2. Application
3. The Functional Calibration Model
3.1. A Simulation Study
References
Chapter 12USEFUL RESULTS FOR THE RENEWALAND THE ALTERNATING RENEWAL PROCESS
Abstract
1. Introduction
2. Notation
3. The Mean Number of Excess Periods in [0, t).
4. The Alternating Renewal Process
5. A Correlated Alternating Renewal Process
6. The Mean Number of Periods in a Three State Renewal Process
7. A Correlated Three Stages Renewal Process
References
Chapter 13CLASSIFICATION OF MULTIVARIATEREPEATED MEASURES DATA WITHTEMPORAL AUTOCORRELATION
Abstract
1. Introduction
2. Classification Rules
2.1. Classification Rules with Structured Mean Vectors
Maximum Likelihood Estimation of d1,d2,V and S:
Classification Rule:
Classification Rule:
Classification Rule:
2.2. Classification Rules with Unstructured Mean Vectors
3. An Example
4. A Simulated Study
References
Chapter 14BAYESIAN ESTIMATION FOR THE AR(1) MODELUSING ASYMMETRIC LOSS FUNCTIONS
Abstract
1. Introduction
2. Linex Loss Functions
3. Rationale Behind the Asymmetric Loss
4. Different Prior Models
4.1. Conjugate Normal Prior and the Behavior of the Linex Risks
4.2. Alternatives to the Conjugate Prior
5. Decision Analysis
6. Data Analysis
References
Chapter 15BAYESIAN MODELLING FOR RECURRENTLIFETIME DATA WITH A NON HOMOGENEOUSPOISSON PROCESS WITH A FRAILTY TERM WITH AGAMMA OR INVERSE GAUSSIAN DISTRIBUTION
Abstract
1. Introduction
2. Model Formulation
2.1. The Model with a Gamma Frailty Distribution
2.2. The Model with an Inverse Gaussian Frailty Distribution
3. A Bayesian Approach
3.1. The Conditional Posterior for the Model with a Gamma Frailty Distribution
3.2. The Conditional Posterior for the Model with a Inverse Gaussian FrailtyDistribution
4. Model Selection
5. The Animal Carcinogenesis Data
6. Estimating the Individual Frailties
7. Concluding Remarks
Acknowledgments
References
Chapter 16LOCAL INFLUENCE FOR MEASUREMENT ERRORREGRESSION MODELS FOR THE ANALYSIS OFPRETEST/POSTTEST DATA
Abstract
1. Introduction
2. Measurement Error Regression Model with Null Intercept
3. Local Influence Diagnostics
3.1. Perturbation of CaseWeights
3.2. Perturbation of the Response Variables
3.3. Perturbation of the Explanatory Variables
3.4. Perturbation of the Variance of the Measurement Errors
4. Numerical Illustration
Appendix A: EM Algorithm
E Step
M Step
Appendix B: Observed Information Matrix
Acknowledgements
References
Chapter 17A TRANSITION MODEL FOR AN ORDEREDCLUSTER OF MIXED CONTINUOUS AND DISCRETERESPONSES WITH NON-MONOTONE MISSINGNESS
Abstract
1. Introduction
2. Psychological Disorders Data
3. Transition Model for Ordered Cluster or Longitudinal Datawith Non-monotone Missing Responses
3.1. Residuals
4. A Transition Model for the Psychological Disorders Data
4.1. The Model
4.2. Likelihood
4.3. Results
5. Discussion
Acknowledgment
References
Chapter 18ON A NONBINARY S-OPTIMAL DESIGN OVER ACLASS OF MINIMALLY CONNECTED BINARYROW-COLUMN DESIGNS
Abstract
1. Introduction
2. Preliminaries
3. s-optimal Minimal Design
4. Concluding Remarks
References
Chapter 19THE ERLANGIAN MACHINE INTERFERENCE MODEL:ER/M/2/K/N WITH BALKING, RENEGING ANDHETEROGENEOUS REPAIRMEN*
Abstract
1. Introduction
2. Analyzing the Problem
3. The Steady-State Equations and Their Solution
4. Special Cases
References
Chapter 20SOME EXTENSIONS TO DOUBLERANKED SET SAMPLING*
Abstract
1. Introduction
2. Sampling Methods
2.1. Ranked Set Sampling
2.2. Median Ranked Set Sampling
2.3. Extreme Ranked Set Sampling
2.4. Double Ranked Set Sampling
2.5. Median Double Ranked Set Sampling
2.6. Double Median Ranked Set Sampling
2.7. Extreme Double Ranked Set Sampling
3. Notations and Some Definitions
4. Median Double Ranked Set Sampling
4.1. Efficiency of MDRSS
4.2. Examples
5. Double Median Ranked Set Sampling
5.1. Efficiency of DMRSS
5.2. Examples
6. Extreme Double Ranked Set Sampling
6.1. Efficiency of EDRSS
6.2. Examples
7. Results and Discussion
Appendix
References
INDEX
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