Autore	Barnett Vic
Edizione	[3rd ed.]
Pubbl/distr/stampa	Chichester ; ; New York, : Wiley, c1999
Descrizione fisica	1 online resource (403 p.)
Disciplina	519.5 519.54
Collana	Wiley series in probability and mathematical statistics
Soggetto topico	Mathematical statistics Statistical decision
ISBN	1-282-30731-2 9786612307317 0-470-31779-5 0-470-85982-2 0-470-31695-0 0-585-31386-5
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Comparative Statistical Inference; Contents; Preface; Preface to Second Edition; Preface to Third Edition; Acknowledgements; Chapter 1. Introduction: Statistical Inference and Decision-making; 1.1 What is Statistics?; 1.2 Probability Models; 1.3 Relevant Information; 1.4 Statistical Inference and Decision-making; 1.5 Different Approaches; 1.6 Arbitrariness and Controversy; 1.7 Historical Comment and Further References; Chapter 2. An Illustration of the Different Approaches; 2.1 A Practical Example; 2.2 Sample Data as the Sole Source of Information: the Classical Approach; 2.2.1 Batch Quality 2.2.2 Component Lifetimes2.3 Relevant Prior Information: the Bayesian Approach; 2.3.1 Prior Information on Batch Quality; 2.3.2 Prior Attitudes about Component Lifetimes; 2.4 Costs and Consequences: Simple Decision Theory Ideas; 2.5 Comment and Comparisons; Chapter 3. Probability; 3.1 Types of Probability; 3.2 'Classical' Probability; 3.3 The Frequency View; 3.4 Logical Probability; 3.5 Subjective Probability; 3.6 Other Viewpoints; 3.6.1 Chaos; 3.6.2 Fuzzy Set Theory; 3.6.3 Risk, Uncertainty and Sensitivity Analysis; 3.7 Some Historical Background; 3.8 And So; 3.9 And Yet Chapter 4. Utility and Decision-making4.1 Setting a Value on Rewards and Consequences; 4.2 The Rational Expression of Preferences; 4.3 Preferences for Prospects and Mixtures of Prospects; 4.4 The Numerical Assessment of Prospects; 4.5 The Measurement of Utilities; 4.5.1 Formal Construction of Utilities; 4.5.2 Personal Expression of Utilities; 4.6 Decision-making; 4.7 The Utility of Money; 4.8 Comment: Mathematical Refinements: Distinctions of Attitude; Chapter 5. Classical Inference; 5.1 Basic Aims and Concepts; 5.1.1 Information and its Representation 5.2 Estimation and Testing Hypotheses-the Dual Aims5.3 Point Estimation; 5.3.1 Criteria for Point Estimators; 5.3.2 Optimum Estimators; 5.3.3 Methods of Constructing Estimators; 5.3.4 Estimating Several Parameters; 5.4 Testing Statistical Hypotheses; 5.4.1 Criteria for Hypothesis Tests; 5.4.2 Uniformly Most Powerful Tests; 5.4.3 Construction of Tests; 5.5 Region and Interval Estimates; 5.6 Ancillarity, Conditionality, Modified forms of Sufficiency and Likelihood; 5.6.1 The Sufficiency, Conditionality and Likelihood Principles; 5.6.2 Modified Likelihood Forms (Marginal, Partial, Profile, etc.) 5.7 Comment and Controversy5.7.1 Initial and Final Precision; 5.7.2 Prediction and Tolerance Regions; 5.7.3 Hypothesis Tests and Decisions; 5.7.4 Counter Criticism; Chapter 6. Bayesian Inference; 6.1 Thomas Bayes; 6.2 The Bayesian Method; 6.3 Particular Techniques; 6.4 Prediction in Bayesian Inference; 6.5 Prior Information; 6.5.1 Prior Ignorance; 6.5.2 Vague Prior Knowledge; 6.5.3 Substantial Prior Knowledge; 6.5.4 Conjugate Prior Distributions; 6.5.5 Quantifying Subjective Prior Information; 6.6 Computing Posterior Distributions; 6.7 Empirical Bayes' methods: Meta-prior Distributions 6.7.1 Empirical Bayes' Methods
Record Nr.	UNINA-9910134833103321

Autore	Barnett Vic
Pubbl/distr/stampa	Chichester, West Sussex, England ; ; Hoboken, NJ, : J. Wiley, c2004
Descrizione fisica	1 online resource (318 p.)
Disciplina	363.70072 519.5
Collana	Wiley series in probability and statistics
Soggetto topico	Mathematical statistics Environmental sciences - Statistical methods
ISBN	1-280-28762-4 9786610287628 0-470-02474-7 0-470-02697-9
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Environmental Statistics; Contents; Preface; Chapter 1 Introduction; 1.1 Tomorrow is too Late!; 1.2 Environmental Statistics; 1.3 Some Examples; 1.3.1 'Getting it all together'; 1.3.2 'In time and space'; 1.3.3 'Keep it simple'; 1.3.4 'How much can we take?'; 1.3.5 'Over the top'; 1.4 Fundamentals; 1.5 Bibliography; PART I EXTREMAL STRESSES: EXTREMES, OUTLIERS, ROBUSTNESS; Chapter 2 Ordering and Extremes: Applications, models, inference; 2.1 Ordering the Sample; 2.1.1 Order statistics; 2.2 Order-based Inference; 2.3 Extremes and Extremal Processes; 2.3.1 Practical study and empirical models generalized extreme-value distributions2.4 Peaks over Thresholds and the Generalized Pareto Distribution; Chapter 3 Outliers and Robustness; 3.1 What is an Outlier?; 3.2 Outlier Aims and Objectives; 3.3 Outlier-Generating Models; 3.3.1 Discordancy and models for outlier generation; 3.3.2 Tests of discordancy for specific distributions; 3.4 Multiple Outliers: Masking and Swamping; 3.5 Accommodation: Outlier-Robust Methods; 3.6 A Possible New Approach to Outliers; 3.7 Multivariate Outliers; 3.8 Detecting Multivariate Outliers; 3.8.1 Principles; 3.8.2 Informal methods; 3.9 Tests of Discordancy 3.10 Accommodation3.11 Outliers in linear models; 3.12 Robustness in General; PART II COLLECTING ENVIRONMENTAL DATA: SAMPLING AND MONITORING; Chapter 4 Finite-Population Sampling; 4.1 A Probabilistic Sampling Scheme; 4.2 Simple Random Sampling; 4.2.1 Estimating the mean, X; 4.2.2 Estimating the variance, S(2); 4.2.3 Choice of sample size, n; 4.2.4 Estimating the population total, X(T); 4.2.5 Estimating a proportion, P; 4.3 Ratios and Ratio Estimators; 4.3.1 The estimation of a ratio; 4.3.2 Ratio estimator of a population total or mean; 4.4 Stratified (simple) Random Sampling 4.4.1 Comparing the simple random sample mean and the stratified sample mean4.4.2 Choice of sample sizes; 4.4.3 Comparison of proportional allocation and optimum allocation; 4.4.4 Optimum allocation for estimating proportions; 4.5 Developments of Survey Sampling; Chapter 5 Inaccessible and Sensitive Data; 5.1 Encountered Data; 5.2 Length-Biased or Size-Biased Sampling and Weighted Distributions; 5.2.1 Weighted distribution methods; 5.3 Composite Sampling; 5.3.1 Attribute Sampling; 5.3.2 Continuous variables; 5.3.3 Estimating mean and variance; 5.4 Ranked-Set Sampling 5.4.1 The ranked-set sample mean5.4.2 Optimal estimation; 5.4.3 Ranked-set sampling for normal and exponential distributions; 5.4.4 Imperfect ordering; Chapter 6 Sampling in the Wild; 6.1 Quadrat Sampling; 6.2 Recapture Sampling; 6.2.1 The Petersen and Chapman estimators; 6.2.2 Capture-recapture methods in open populations; 6.3 Transect Sampling; 6.3.1 The simplest case: strip transects; 6.3.2 Using a detectability function; 6.3.3 Estimating f (y); 6.3.4 Modifications of approach; 6.3.5 Point transects or variable circular plots; 6.4 Adaptive Sampling 6.4.1 Simple models for adaptive sampling
Record Nr.	UNINA-9910143557803321

Autore	Barnett Vic
Pubbl/distr/stampa	Chichester, West Sussex, England ; ; Hoboken, NJ, : J. Wiley, c2004
Descrizione fisica	1 online resource (318 p.)
Disciplina	363.70072 519.5
Collana	Wiley series in probability and statistics
Soggetto topico	Mathematical statistics Environmental sciences - Statistical methods
ISBN	1-280-28762-4 9786610287628 0-470-02474-7 0-470-02697-9
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Environmental Statistics; Contents; Preface; Chapter 1 Introduction; 1.1 Tomorrow is too Late!; 1.2 Environmental Statistics; 1.3 Some Examples; 1.3.1 'Getting it all together'; 1.3.2 'In time and space'; 1.3.3 'Keep it simple'; 1.3.4 'How much can we take?'; 1.3.5 'Over the top'; 1.4 Fundamentals; 1.5 Bibliography; PART I EXTREMAL STRESSES: EXTREMES, OUTLIERS, ROBUSTNESS; Chapter 2 Ordering and Extremes: Applications, models, inference; 2.1 Ordering the Sample; 2.1.1 Order statistics; 2.2 Order-based Inference; 2.3 Extremes and Extremal Processes; 2.3.1 Practical study and empirical models generalized extreme-value distributions2.4 Peaks over Thresholds and the Generalized Pareto Distribution; Chapter 3 Outliers and Robustness; 3.1 What is an Outlier?; 3.2 Outlier Aims and Objectives; 3.3 Outlier-Generating Models; 3.3.1 Discordancy and models for outlier generation; 3.3.2 Tests of discordancy for specific distributions; 3.4 Multiple Outliers: Masking and Swamping; 3.5 Accommodation: Outlier-Robust Methods; 3.6 A Possible New Approach to Outliers; 3.7 Multivariate Outliers; 3.8 Detecting Multivariate Outliers; 3.8.1 Principles; 3.8.2 Informal methods; 3.9 Tests of Discordancy 3.10 Accommodation3.11 Outliers in linear models; 3.12 Robustness in General; PART II COLLECTING ENVIRONMENTAL DATA: SAMPLING AND MONITORING; Chapter 4 Finite-Population Sampling; 4.1 A Probabilistic Sampling Scheme; 4.2 Simple Random Sampling; 4.2.1 Estimating the mean, X; 4.2.2 Estimating the variance, S(2); 4.2.3 Choice of sample size, n; 4.2.4 Estimating the population total, X(T); 4.2.5 Estimating a proportion, P; 4.3 Ratios and Ratio Estimators; 4.3.1 The estimation of a ratio; 4.3.2 Ratio estimator of a population total or mean; 4.4 Stratified (simple) Random Sampling 4.4.1 Comparing the simple random sample mean and the stratified sample mean4.4.2 Choice of sample sizes; 4.4.3 Comparison of proportional allocation and optimum allocation; 4.4.4 Optimum allocation for estimating proportions; 4.5 Developments of Survey Sampling; Chapter 5 Inaccessible and Sensitive Data; 5.1 Encountered Data; 5.2 Length-Biased or Size-Biased Sampling and Weighted Distributions; 5.2.1 Weighted distribution methods; 5.3 Composite Sampling; 5.3.1 Attribute Sampling; 5.3.2 Continuous variables; 5.3.3 Estimating mean and variance; 5.4 Ranked-Set Sampling 5.4.1 The ranked-set sample mean5.4.2 Optimal estimation; 5.4.3 Ranked-set sampling for normal and exponential distributions; 5.4.4 Imperfect ordering; Chapter 6 Sampling in the Wild; 6.1 Quadrat Sampling; 6.2 Recapture Sampling; 6.2.1 The Petersen and Chapman estimators; 6.2.2 Capture-recapture methods in open populations; 6.3 Transect Sampling; 6.3.1 The simplest case: strip transects; 6.3.2 Using a detectability function; 6.3.3 Estimating f (y); 6.3.4 Modifications of approach; 6.3.5 Point transects or variable circular plots; 6.4 Adaptive Sampling 6.4.1 Simple models for adaptive sampling
Record Nr.	UNINA-9910831188103321

Autore	Barnett Vic
Pubbl/distr/stampa	Chichester, West Sussex, England ; ; Hoboken, NJ, : J. Wiley, c2004
Descrizione fisica	1 online resource (318 p.)
Disciplina	519.5
Collana	Wiley series in probability and statistics
Soggetto topico	Mathematical statistics Environmental sciences - Statistical methods
ISBN	9786610287628 9781280287626 1280287624 9780470024744 0470024747 9780470026977 0470026979
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Environmental Statistics; Contents; Preface; Chapter 1 Introduction; 1.1 Tomorrow is too Late!; 1.2 Environmental Statistics; 1.3 Some Examples; 1.3.1 'Getting it all together'; 1.3.2 'In time and space'; 1.3.3 'Keep it simple'; 1.3.4 'How much can we take?'; 1.3.5 'Over the top'; 1.4 Fundamentals; 1.5 Bibliography; PART I EXTREMAL STRESSES: EXTREMES, OUTLIERS, ROBUSTNESS; Chapter 2 Ordering and Extremes: Applications, models, inference; 2.1 Ordering the Sample; 2.1.1 Order statistics; 2.2 Order-based Inference; 2.3 Extremes and Extremal Processes; 2.3.1 Practical study and empirical models generalized extreme-value distributions2.4 Peaks over Thresholds and the Generalized Pareto Distribution; Chapter 3 Outliers and Robustness; 3.1 What is an Outlier?; 3.2 Outlier Aims and Objectives; 3.3 Outlier-Generating Models; 3.3.1 Discordancy and models for outlier generation; 3.3.2 Tests of discordancy for specific distributions; 3.4 Multiple Outliers: Masking and Swamping; 3.5 Accommodation: Outlier-Robust Methods; 3.6 A Possible New Approach to Outliers; 3.7 Multivariate Outliers; 3.8 Detecting Multivariate Outliers; 3.8.1 Principles; 3.8.2 Informal methods; 3.9 Tests of Discordancy 3.10 Accommodation3.11 Outliers in linear models; 3.12 Robustness in General; PART II COLLECTING ENVIRONMENTAL DATA: SAMPLING AND MONITORING; Chapter 4 Finite-Population Sampling; 4.1 A Probabilistic Sampling Scheme; 4.2 Simple Random Sampling; 4.2.1 Estimating the mean, X; 4.2.2 Estimating the variance, S(2); 4.2.3 Choice of sample size, n; 4.2.4 Estimating the population total, X(T); 4.2.5 Estimating a proportion, P; 4.3 Ratios and Ratio Estimators; 4.3.1 The estimation of a ratio; 4.3.2 Ratio estimator of a population total or mean; 4.4 Stratified (simple) Random Sampling 4.4.1 Comparing the simple random sample mean and the stratified sample mean4.4.2 Choice of sample sizes; 4.4.3 Comparison of proportional allocation and optimum allocation; 4.4.4 Optimum allocation for estimating proportions; 4.5 Developments of Survey Sampling; Chapter 5 Inaccessible and Sensitive Data; 5.1 Encountered Data; 5.2 Length-Biased or Size-Biased Sampling and Weighted Distributions; 5.2.1 Weighted distribution methods; 5.3 Composite Sampling; 5.3.1 Attribute Sampling; 5.3.2 Continuous variables; 5.3.3 Estimating mean and variance; 5.4 Ranked-Set Sampling 5.4.1 The ranked-set sample mean5.4.2 Optimal estimation; 5.4.3 Ranked-set sampling for normal and exponential distributions; 5.4.4 Imperfect ordering; Chapter 6 Sampling in the Wild; 6.1 Quadrat Sampling; 6.2 Recapture Sampling; 6.2.1 The Petersen and Chapman estimators; 6.2.2 Capture-recapture methods in open populations; 6.3 Transect Sampling; 6.3.1 The simplest case: strip transects; 6.3.2 Using a detectability function; 6.3.3 Estimating f (y); 6.3.4 Modifications of approach; 6.3.5 Point transects or variable circular plots; 6.4 Adaptive Sampling 6.4.1 Simple models for adaptive sampling
Record Nr.	UNINA-9911020320903321