Industrial statistics : aims and computational aspects : proceedings of the satellite conference to the 51st session of the International Statistical Institute (ISI), Athens, Greece, August 16-17, 1997
著者
書誌事項
Industrial statistics : aims and computational aspects : proceedings of the satellite conference to the 51st session of the International Statistical Institute (ISI), Athens, Greece, August 16-17, 1997
（Contributions to statistics）
Physica-Verlag, 1997
大学図書館所蔵 全11件
注記
Papers presented at the International Conference on Industrial Statistics, held in Athens, Aug. 16-17, 1997 and organized as a satellite conference to the 51st session of the International Statistical Institute, held in 1997 in Istanbul
内容説明・目次
内容説明
Devoted to the growing impact of statistical methodology and statistical computing in industry the aim of this book is to link the three components: Statistics - industry - computers. Different areas of industrial statistics are presented by a number of excellent contributions. The following topics are covered: Quality control, engineering and monitoring; reliability and failure time analysis, experimental design; repeated measurements - multiple inference; pharma - statistics; computing, imaging and perception. This book concentrates on the interface between statistical needs in industry and statistical methods developed by statisticians and engineers.
目次
- Quality Control, Engineering and Monitoring: S.H. Park, J.J. Kim: Quality Engineering Using Robust Design and Analysis
- C.P. Kitsos, V.L. Nini: The Calibration Problem in Industry
- C. Vourvahi, J. Voutsinas, J. Kiriakidis: Case Study and Applying Statistical Techniques for the Quality Assurance in a Paint Industry
- E.B. Martin and A.J. Morris: Taking Multivariate Statistics out into Industry - Multivariate Statistical Progress Control and Process Performance Monitoring
- S. Uhlig: Robust Estimation of Variance Components with High Breakdown Point in the 1-Way Random Effect Model
- I.N. Vuchkov, L.N. Boyadjieva: Sources of Inaccuracy in the Mean and Variance Models for Quality Improvement Problems.- Reliability and Failure Time Analysis: W.T. Huang, H.T. Lin: Accelerated Life Test with Some Parameter Change in Life Stress Relation
- J.A. Achcar, J.C. Fogo: Accurate Inferences for the Reliability Function Considering Accelerated Life Tests
- J. Antoch, J. Machek: Prediction of Failures that Have Never Occured - Exponential Case
- A.M. Andronov: Algorithm of Confidence Limits Calculation for the Probability of the Value 1 of a Monotone Boolean Function of Random Variables
- P. Erto, A. Lanzotti, M. Staiano: Developing a Graphical Interface for Pre-Posterior.- Experimental Design: C.P. Kitsos: Nonlinear-Optimal-Sequential Experiment Designs and Applications
- C.H. Muller: Robust Inference and Experimental Design for Multi-Factor Models
- C. Koukouvinos: Construction of Some New Orthogonal Main-Effect Designs
- C. Mortarino, L. Salmaso: Extended V-robustness for Two-level Orthogonal Resolution V Designs
- E. Riccomagno, H.P. Wynn: Computational Algebraic Geometry in Industrial Experimental Design.- Pharmaceutical Statistics: L.A. Hothorn: New Statistical Methods for Analyzing Mutagenicity Assays Real data Problems in Biopharmaceutical Drug Development
- U. Roemisch, S. Gargova: Application of Statistical Selection Procedures inBiotechnology
- L. Edler: Modeling and Computation in Pharmaceutical Statistics when Analyzing Drug Safety
- C. Hirotsu: Isotonic Inference with Particular Interest in Application to Clinical Trials
- G. Heimann: Tests for Linearity and Tests for Zero Slope in Crossover Studies.- Repeated Measurements - Multiple Inference: F. Pesarin: A Nonparametric Combination Method for Dependent Permutation Tests with Application to Some Problems with Repeated Measures
- M. Neuhauser, L.A. Hothorn: Adaptive Tests for Trend.- Computing, Imaging and Prediction: G. Yin: Convergence Rates of Simulated Annealing-Type of Recursive Algorithms
- H. Lauschmann, V. Benes: Spatial Statistics in the Material research
- G. Celant: Exact Solutions to the Problem of Predicting a vast Class of Weakly Stationary, Linearly Singular, Discrete Parameter Stochastic Processes.
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