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020			_a3319433156
020			_a3319433172 _q(ebk)
020			_a9783319433158
020			_a9783319433172
020			_z3319433156
035			_a(Uk)019091150
037			_acom.springer.onix.9783319433172 _bSpringer Nature
040			_aIDEBK _beng _cIDEBK _dDKDLA _dOCLCO _dYDX _dNJR _dVT2 _dOCLCO _dOCLCQ _dVLB _dOCLCF _dUk _erda
042			_aukblsr
050		4	_aQA273.19.E4
082	0	4	_a519.2 _223
245	0	0	_aComputational probability applications / _c[edited by] Andrew G. Glen, Lawrence M. Leemis
264		1	_aSwitzerland : _bSpringer, _c2017.
264		4	_c©2017
300			_a1 online resource (258 pages) : _billustrations, tables.
336			_atext _2rdacontent
337			_acomputer _2rdamedia
338			_aonline resource _2rdacarrier
490	1		_aInternational Series in Operations Research & Management Science ; _vVolume 247
504			_aIncludes bibliographical references and index.
505	0		_aPreface; Contents; 1 Accurate Estimation with One Order Statistic; 1.1 Introduction; 1.2 The Case of the Exponential Distribution; 1.3 An Example for the Exponential Distribution; 1.4 The Rayleigh and Weibull Distribution Extensions; 1.5 Simulations and Computational Issues; 1.6 Implications for Design of Life Tests; 1.7 Conclusions; 2 On the Inverse Gamma as a Survival Distribution ; 2.1 Introduction; 2.2 Probabilistic Properties; 2.3 Statistical Inference; 2.3.1 Complete Data Sets; 2.3.2 Censored Data Sets; 2.4 Conclusions; 3 Order Statistics in Goodness-of-Fit Testing ; 3.1 Introduction
505	8		_a3.2 P-Vector3.3 Computation of the P-Vector ; 3.4 Goodness-of-Fit Testing; 3.5 Power Estimates for Test Statistics; 3.6 Further Research; 4 The ``Straightforward'' Nature of Arrival Rate Estimation?; 4.1 Introduction; 4.1.1 Sampling Plan 1: Time Sampling; 4.1.2 Sampling Plan 2: Count Sampling; 4.1.3 Sampling Plan 3: Limit Both Time and Arrivals; 4.2 Conclusions; 5 Survival Distributions Based on the Incomplete Gamma Function Ratio ; 5.1 Introduction; 5.2 Properties and Results; 5.3 Examples; 5.4 Conclusions
505	8		_a6 An Inference Methodology for Life Tests with Full Samples or Type II Right Censoring 6.1 Introduction and Literature Review; 6.2 The Methodology for Censored Data; 6.3 The Uniformity Test Statistic; 6.4 Implementation Using APPL; 6.5 Power Simulation Results; 6.6 Some Applications and Implications; 6.7 Conclusions and Further Research; 7 Maximum Likelihood Estimation Using Probability Density Functions of Order Statistics ; 7.1 Introduction; 7.2 MLEOS with Complete Samples; 7.3 Applying MLEOS to Censored Samples; 7.4 Conclusions and Further Research; 8 Notes on Rank Statistics
505	8		_a8.1 Introduction8.2 Explanation of the Tests; 8.3 Distribution of the Test Statistic Under H0; 8.4 Wilcoxon Power Curves for n = 2; 8.5 Generalization to Larger Sample Sizes; 8.6 Comparisons and Analysis; 8.7 The Wilcoxon-Mann-Whitney Test; 8.8 Explanation of the Test; 8.9 Three Cases of the Distribution of W Under H0; 8.9.1 Case I: No Ties; 8.9.2 Case II: Ties Only Within Each Sample; 8.9.3 Case III: Ties Between Both Samples; 8.10 Conclusions; 9 Control Chart Constants for Non-normal Sampling ; 9.1 Introduction; 9.2 Constants d2, d3; 9.3 Constants c4, c5; 9.3.1 Normal Sampling
505	8		_a9.3.2 Non-normal Sampling9.4 Conclusions; 10 Linear Approximations of Probability DensityFunctions; 10.1 Approximating a PDF; 10.2 Methods for Endpoint Placement; 10.2.1 Equal Spacing; 10.2.2 Placement by Percentiles; 10.2.3 Curvature-Based Approach; 10.2.4 Optimization-Based Approach; 10.3 Comparison of the Methods; 10.4 Application; 10.4.1 Convolution Theorem; 10.4.2 Monte Carlo Approximation; 10.4.3 Convolution of Approximate PDFs; 10.5 Conclusions; 11 Univariate Probability Distributions ; 11.1 Introduction; 11.2 Discussion of Properties; 11.3 Discussion of Relationships
520			_aThis focuses on the developing field of building probability models with the power of symbolic algebra systems. The book combines the uses of symbolic algebra with probabilistic/stochastic application and highlights the applications in a variety of contexts. The research explored in each chapter is unified by the use of A Probability Programming Language (APPL) to achieve the modeling objectives. APPL, as a research tool, enables a probabilist or statistician the ability to explore new ideas, methods, and models. Furthermore, as an open-source language, it sets the foundation for future algorithms to augment the original code. Computational Probability Applications is comprised of fifteen chapters, each presenting a specific application of computational probability using the APPL modeling and computer language. The chapter topics include using inverse gamma as a survival distribution, linear approximations of probability density functions, and also moment-ratio diagrams for univariate distributions. These works highlight interesting examples, often done by undergraduate students and graduate students that can serve as templates for future work. In addition, this book should appeal to researchers and practitioners in a range of fields including probability, statistics, engineering, finance, neuroscience, and economics
650		0	_aBusiness and Management
650		0	_aBusiness.
650		0	_aDecision making.
650		0	_aDistribution (Probability theory)
650		0	_aManagement science.
650		0	_aMathematical statistics.
650		0	_aOperation Research/Decision Theory
650		0	_aOperations research.
650		0	_aProbabilities.
650		0	_aProbability Theory and Stochastic Processes
650		0	_aStatistics and Computing/Statistics Programs
650		0	_aStatistics.
650		7	_aBUSINESS & ECONOMICS / Management. _2bisacsh
650		7	_aBUSINESS & ECONOMICS / Reference. _2bisacsh
650		7	_aBUSINESS & ECONOMICS / Skills. _2bisacsh
650		7	_aBusiness & Economics _xOperations Research. _2bisacsh
650		7	_aBusiness. _2fast _0(OCoLC)fst00842262
650		7	_aComputers _xMathematical & Statistical Software. _2bisacsh
650		7	_aDecision making. _2fast _0(OCoLC)fst00889035
650		7	_aMathematical & statistical software. _2bicssc
650		7	_aMathematics _xProbability & Statistics _xGeneral. _2bisacsh
650		7	_aOperational research. _2bicssc
650		7	_aOperations research. _2fast _0(OCoLC)fst01046387
650		7	_aProbabilities. _2fast _0(OCoLC)fst01077737
650		7	_aProbability & statistics. _2bicssc
650		7	_aStatistics. _2fast _0(OCoLC)fst01132103
655		4	_aElectronic books.
700	1		_aGlen, Andrew G., _eeditor.
700	1		_aLeemis, Lawrence M., _eeditor.
830		0	_aInternational series in operations research & management science ; _vVolume 247.
856			_uhttps://drive.google.com/file/d/17Q-jkLY4FB3ZGK7ErfhyjocbpXQ--S93/view?usp=sharing
859			_aELD
884			_aLDL ebooks ONIX to marcxml transformation using Record_Load-eBooks_Legal_Deposit_onix2marc_v2-1.xsl _g20181015 _kcom.springer.onix.9783319433172 _qUk
889			_a(OCoLC)967394853
999			_c12195 _d12195