eBook International Encyclopedia of Statistical Science, 1st Edition

  • Miodrag Lovric
  • Published By:
  • ISBN-10: 3642048986
  • ISBN-13: 9783642048982
  • DDC: 519.503
  • Grade Level Range: College Freshman - College Senior
  • 1673 Pages | eBook
  • Original Copyright 2011 | Published/Released December 2013
  • This publication's content originally published in print form: 2011
  • Price:  Sign in for price

About

Overview

The goal of this book is multidimensional: a) to help reviving Statistics education in many parts in the world where it is in crisis. For the first time authors from many developing countries have an opportunity to write together with the most prominent world authorities. The editor has spent several years searching for the most reputable statisticians all over the world. International contributors are either presidents of the local statistical societies, or head of the Statistics department at the main university, or the most distinguished statisticians in their countries. b) to enable any non-statistician to obtain quick and yet comprehensive and highly understandable view on certain statistical term, method or application c) to enable all the researchers, managers and practitioners to refresh their knowledge in Statistics, especially in certain controversial fields. d) to revive interest in statistics among students, since they will see its usefulness and relevance in almost all branches of Science.

Features and Benefits

  • The 3 volumes present contributions by 617 statisticians and educators from 105 countries, including 4 Nobel laureates.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Other Frontmatter.
Copyright Page.
Dedication.
Foreword by Bradley Efron the Future of Statistics.
Foreword by Rajko Kuzmanović.
Preface.
About the Editor.
List of Contributors.
1: Absolute Penalty Estimation.
2: Accelerated Lifetime Testing.
3: Acceptance Sampling.
4: Actuarial Methods.
5: Adaptive Linear Regression.
6: Adaptive Methods.
7: Adaptive Sampling.
8: Advantages of Bayesian Structuring: Estimating Ranks and Histograms.
9: African Population Censuses.
10: Aggregation Schemes.
11: Agriculture, Statistics in.
12: Akaike's Information Criterion.
13: Akaike's Information Criterion: Background, Derivation, Properties, and Refinements.
14: Algebraic Statistics.
15: Almost Sure Convergence of Random Variables.
16: Analysis of Areal and Spatial Interaction Data.
17: Analysis of Covariance.
18: Analysis of Multivariate Agricultural Data.
19: Analysis of Variance.
20: Analysis of Variance Model, Effects of Departures from Assumptions Underlying.
21: Anderson–Darling Tests of Goodness-of-Fit.
22: Approximations for Densities of Sufficient Estimators.
23: Approximations to Distributions.
24: Association Measures for Nominal Categorical Variables.
25: Astrostatistics.
26: Asymptotic Normality.
27: Asymptotic Relative Efficiency in Estimation.
28: Asymptotic Relative Efficiency in Testing.
29: Asymptotic, Higher Order.
30: Autocorrelation in Regression.
31: Axioms of Probability.
32: Balanced Sampling.
33: Banking, Statistics in.
34: Bartlett and Bartlett-Type Corrections.
35: Bartlett's Test.
36: Bayes' Theorem.
37: Bayesian Analysis or Evidence Based Statistics?.
38: Bayesian Approach of the Unit Root Test.
39: Bayesian Nonparametric Statistics.
40: Bayesian P-Values.
41: Bayesian Reliability Modeling.
42: Bayesian Semiparametric Regression.
43: Bayesian Statistics.
44: Bayesian Versus Frequentist Statistical Reasoning.
45: Bayesian vs. Classical Point Estimation: A Comparative Overview.
46: Behrens–Fisher Problem.
47: Best Linear Unbiased Estimation in Linear Models.
48: Beta Distribution.
49: Bias Analysis.
50: Bias Correction.
51: Binomial Distribution.
52: Bioinformatics.
53: Biopharmaceutical Research, Statistics in.
54: Biostatistics.
55: Bivariate Distributions.
56: Bootstrap Asymptotics.
57: Bootstrap Methods.
58: Borel–Cantelli Lemma and Its Generalizations.
59: Box–Cox Transformation.
60: Box–Jenkins Time Series Models.
61: Brownian Motion and Diffusions.
62: Business Forecasting Methods.
63: Business Intelligence.
64: Business Statistics.
65: Business Surveys.
66: Calibration.
67: Canonical Analysis and Measures of Association.
68: Canonical Correlation Analysis.
69: Careers in Statistics.
70: Case-Control Studies.
71: Categorical Data Analysis.
72: Causal Diagrams.
73: Causation and Causal Inference.
74: Censoring Methodology.
75: Census.
76: Central Limit Theorems.
77: Chaotic Modelling.
78: Characteristic Functions.
79: Chebyshev's Inequality.
80: Chemometrics.
81: Chernoff Bound.
82: Chernff Faces.
83: Chernoff-Savage Theorem.
84: Chi-Square Distribution.
85: Chi-Square Goodness-of-Fit Tests: Drawbacks and Improvements.
86: Chi-Square Test: Analysis of Contingency Tables.
87: Chi-Square Tests.
88: Clinical Trials, History of.
89: Clinical Trials: An Overview.
90: Clinical Trials: Some Aspects of Public Interest.
91: Cluster Analysis: An Introduction.
92: Cluster Sampling.
93: Coefficient of Variation.
94: Collapsibility.
95: Comparability of Statistics.
96: Complier-Average Causal Effect (CACE) Estimation.
97: Components of Statistics.
98: Composite Indicators.
99: Computational Statistics.
100: Conditional Expectation and Probability.
101: Confidence Distributions.
102: Confidence Interval.
103: Confounding and Confounder Control.
104: Contagious Distributions.
105: Continuity Correction.
106: Control Charts.
107: Convergence of Random Variables.
108: Cook's Distance.
109: Copulas.
110: Copulas in Finance.
111: Copulas: Distribution Functions and Simulation.
112: Cornish–Fisher Expansions.
113: Correlation Coefficient.
114: Correspondence Analysis.
115: Cp Statistic.
116: Cramér–Rao Inequality.
117: Cramér–Von Mises Statistics for Discrete Distributions.
118: Cross Classified and Multiple Membership Multilevel Models.
119: Cross-Covariance Operators.
120: Data Analysis.
121: Data Depth.
122: Data Mining.
123: Data Mining Time Series Data.
124: Data Privacy and Confidentiality.
125: Data Quality (Poor Quality Data: The Fly in the Data Analytics Ointment).
126: Decision Theory: An Introduction.
127: Decision Theory: An Overview.
128: Decision Trees for the Teaching of Statistical Estimation.
129: Degradation Models in Reliability and Survival Analysis.
130: Degrees of Freedom.
131: Degrees of Freedom in Statistical Inference.
132: Demographic Analysis: A Stochastic Approach.
133: Demography.
134: Density Ratio Model.
135: Design for Six Sigma.
136: Design of Experiments: A Pattern of Progress.
137: Designs for Generalized Linear Models.
138: Detecting Outliers in Time Series Using Simulation.
139: Detection of Turning Points in Business Cycles.
140: Dickey-Fuller Tests.
141: Discriminant Analysis: An Overview.
142: Discriminant Analysis: Issues and Problems.
143: Dispersion Models.
144: Distance Measures.
145: Distance Sampling.
146: Distributions of Order k.
147: Diversity.
148: Divisible Statistics.
149: Dummy Variables.
150: Durbin–Watson Test.
151: Econometrics.
152: Econometrics: A Failed Science?.
153: Economic Growth and Well-Being: Statistical Perspective.
154: Economic Statistics.
155: Edgeworth Expansion.
156: Effect Modification and Biological Interaction.
157: Effect Size.
158: Eigenvalue, Eigenvector and Eigenspace.
159: Empirical Likelihood Approach to Inference from Sample Survey Data.
160: Empirical Processes.
161: Entropy.
162: Entropy and Cross Entropy as Diversity and Distance Measures.
163: Environmental Monitoring, Statistics Role in.
164: Equivalence Testing.
165: Ergodic Theorem.
166: Erlang's Formulas.
167: Estimation.
168: Estimation Problems for Random Fields.
169: Estimation: An Overview.
170: Eurostat.
171: Event History Analysis.
172: Exact Goodness-of-Fit Tests Based on Sufficiency.
173: Exact Inference for Categorical Data.
174: Exchangeability.
175: Expected Value.
176: Experimental Design: An Introduction.
177: Expert Systems.
178: Explaining Paradoxes in Nonparametric Statistics.
179: Exploratory Data Analysis.
180: Exponential and Holt-Winters Smoothing.
181: Exponential Family Models.
182: Extreme Value Distributions.
183: Extremes of Gaussian Processes.
184: F Distribution.
185: Factor Analysis and Latent Variable Modelling.
186: Factorial Experiments.
187: False Discovery Rate.
188: Farmer Participatory Research Designs.
189: Federal Statistics in the United States, Some Challenges.
1: Gamma Distribution.
2: Gaussian Processes.
3: Gauss-Markov Theorem.
4: General Linear Models.
5: Generalized Extreme Value Family of Probability Distributions.
6: Generalized Hyperbolic Distributions.
7: Generalized Linear Models.
8: Generalized Quasi-Likelihood (GQL) Inferences.
9: Generalized Rayleigh Distribution.
10: Generalized Weibull Distributions.
11: Geometric and Negative Binomial Distributions.
12: Geometric Mean.
13: Geostatistics and Kriging Predictors.
14: Glivenko-Cantelli Theorems.
15: Graphical Analysis of Variance.
16: Graphical Markov Models.
17: Handling with Missing Observations in Simple Random Sampling and Ranked Set Sampling.
18: Harmonic Mean.
19: Hazard Ratio Estimator.
20: Hazard Regression Models.
21: Heavy-Tailed Distributions.
22: Heteroscedastic Time Series.
23: Heteroscedasticity.
24: Hierarchical Clustering.
25: Hodges-Lehmann Estimators.
26: Horvitz–Thompson Estimator.
27: Hotelling's T Statistic.
28: Hyperbolic Secant Distributions and Generalizations.
29: Hypergeometric Distribution and Its Application in Statistics.
30: Identifiability.
31: Imprecise Probability.
32: Imprecise Reliability.
33: Imputation.
34: Incomplete Block Designs.
35: Incomplete Data in Clinical and Epidemiological Studies.
36: Index Numbers.
37: Industrial Statistics.
38: Inference Under Informative Probability Sampling.
39: Influential Observations.
40: Information Theory and Statistics.
41: Instrumental Variables.
42: Insurance, Statistics in.
43: Integrated Statistical Databases.
44: Interaction.
45: Interactive and Dynamic Statistical Graphics.
46: Internet Survey Methodology: Recent Trends and Developments.
47: Intervention Analysis in Time Series.
48: Intraclass Correlation Coefficient.
49: Inverse Gaussian Distribution.
50: Inverse Sampling.
51: Inversion of Bayes' Formula for Events.
52: Itô Integral.
53: Jackknife.
54: James–Stein Estimator.
55: Jarque-Bera Test.
56: Jump Regression Analysis.
57: Kalman Filtering.
58: Kaplan-Meier Estimator.
59: Kappa Cofficient of Agreement.
60: Kendall's Tau.
61: Khmaladze Transformation.
62: Kolmogorov-Smirnov Test.
63: Kullback-Leibler Divergence.
64: Kurtosis: An Overview.
65: Large Deviations and Applications.
66: Laws of Large Numbers.
67: Learning Statistics in a Foreign Language.
68: Least Absolute Residuals Procedure.
69: Least Squares.
70: Lévy Processes.
71: Life Expectancy.
72: Life Table.
73: Likelihood.
74: Limit Theorems of Probability Theory.
75: Linear Mixed Models.
76: Linear Regression Models.
77: Local Asymptotic Mixed Normal Family.
78: Location-Scale Distributions.
79: Logistic Normal Distribution.
80: Logistic Regression.
81: Logistic Distribution.
82: Lorenz Curve.
83: Loss Function.
84: Margin of Error.
85: Marginal Probability: Its Use in Bayesian Statistics as Model Evidence.
86: Marine Research, Statistics in.
87: Markov Chain Monte Carlo.
88: Markov Chains.
89: Markov Processes.
90: Martingale Central Limit Theorem.
91: Martingales.
92: Mathematical and Statistical Modeling of Global Warming.
93: Maximum Entropy Method for Estimation of Missing Data.
94: Mean, Median and Mode.
95: Mean, Median, Mode: An Introduction.
96: Mean Residual Life.
97: Measure Theory in Probability.
98: Measurement Error Models.
99: Measurement of Economic Progress.
100: Measurement of Uncertainty.
101: Measures of Agreement.
102: Measures of Dependence.
103: Median Filters and Extensions.
104: Medical Research, Statistics in.
105: Medical Statistics.
106: Meta-Analysis.
107: Method Comparison Studies.
108: Methods of Moments Estimation.
109: Minimum Variance Unbiased.
110: Misuse and Misunderstandings of Statistics.
111: Misuse of Statistics.
112: Mixed Membership Models.
113: Mixture Models.
114: Model Selection.
115: Model-Based Geostatistics.
116: Modeling Count Data.
117: Modeling Randomness Using System Dynamics Concepts.
118: Modeling Survival Data.
119: Models for Z+-Valued Time Series Based on Thinning.
120: Moderate Deviations.
121: Moderating and Mediating Variables in Psychological Research.
122: Moment Generating Function.
123: Monte Carlo Methods in Statistics.
124: Monty Hall Problem: Solution.
125: Mood Test.
126: Most Powerful Test.
127: Moving Averages.
128: Multicollinearity.
129: Multicriteria Clustering.
130: Multicriteria Decision Analysis.
131: Multidimensional Scaling.
132: Multidimensional Scaling: An Introduction.
133: Multilevel Analysis.
134: Multinomial Distribution.
135: Multi-Party Inference and Uncongeniality.
136: Multiple Comparison.
137: Multiple Comparisons Testing from a Bayesian Perspective.
138: Multiple Imputation.
139: Multiple Statistical Decision Theory.
140: Multistage Sampling.
141: Multivariable Fractional Polynomial Models.
142: Multivariate Analysis of Variance (MANOVA).
143: Multivariate Data Analysis: An Overview.
144: Multivariate Normal Distributions.
145: Multivariate Outliers.
146: Multivariate Rank Procedures: Perspectives and Prospectives.
147: Multivariate Reduced-Rank Regression.
148: Multivariate Statistical Analysis.
149: Multivariate Statistical Distributions.
150: Multivariate Statistical Process Control.
151: Multivariate Statistical Simulation.
152: Multivariate Techniques: Robustness.
153: National Account Statistics.
154: Network Models in Probability and Statistics.
155: Network Sampling.
156: Neural Networks.
157: Neyman-Pearson Lemma.
158: Nonlinear Mixed Effects Models.
159: Nonlinear Models.
160: Nonlinear Regression.
161: Nonlinear Time Series Analysis.
162: Nonparametric Density Estimation.
163: Nonparametric Estimation.
164: Nonparametric Estimation Based on Incomplete Observations.
165: Nonparametric Models for ANOVA and ANCOVA Designs.
166: Nonparametric Predictive Inference.
167: Nonparametric Rank Tests.
168: Nonparametric Regression Based on Ranks.
169: Nonparametric Regression Using Kernel and Spline Methods.
170: Nonparametric Statistical Inference.
171: Non-Probability Sampling Survey Methods.
172: Nonresponse in Surveys.
173: Nonresponse in Web Surveys.
174: Nonsampling Errors in Surveys.
175: Non-Uniform Random Variate Generations.
176: Normal Distribution, Univariate.
177: Normal Scores.
178: Normality Tests.
179: Normality Tests: Power Comparison.
180: Null-Hypothesis Significance Testing: Misconceptions.
181: Numerical Integration.
182: Numerical Methods for Stochastic Differential Equations.
183: Omnibus Test for Departures from Normality.
184: Online Statistics Education.
185: Optimal Designs for Estimating Slopes.
186: Optimal Regression Design.
187: Optimal Shrinkage Estimation.
188: Optimal Shrinkage Preliminary Test Estimation.
189: Optimal Statistical Inference in Financial Engineering.
190: Optimal Stopping Rules.
191: Optimality and Robustness in Statistical Forecasting.
192: Optimum Experimental Design.
193: Order Statistics.
194: Ordered Statistical Data: Recent Developments.
195: Outliers.
196: Panel Data.
197: Parametric and Nonparametric Reliability Analysis.
198: Parametric Versus Nonparametric Tests.
199: Pareto Sampling.
200: Partial Least Squares Regression Versus Other Methods.
1: Quantitative Risk Management.
2: Questionnaire.
3: Queueing Theory.
4: R Language.
5: Radon–Nikodým Theorem.
6: Random Coefficient Models.
7: Random Field.
8: Random Matrix Theory.
9: Random Permutations and Partition Models.
10: Random Variable.
11: Random Walk.
12: Randomization.
13: Randomization Tests.
14: Rank Transformations.
15: Ranked Set Sampling.
16: Ranking and Selection Procedures and Related Inference Problems.
17: Ranks.
18: Rao–Blackwell Theorem.
19: Rating Scales.
20: Record Statistics.
21: Recursive Partitioning.
22: Regression Diagnostics.
23: Regression Models with Increasing Numbers of Unknown Parameters.
24: Regression Models with Symmetrical Errors.
25: Relationship Between Statistical and Engineering Process Control.
26: Relationships Among Univariate Statistical Distributions.
27: Renewal Processes.
28: Repeated Measures.
29: Representative Samples.
30: Research Designs.
31: Residuals.
32: Response Surface Methodology.
33: Ridge and Surrogate Ridge Regressions.
34: Rise of Statistics in the Twenty First Century.
35: Risk Analysis.
36: Robust Inference.
37: Robust Regression Estimation in Generalized Linear Models.
38: Robust Statistical Methods.
39: Robust Statistics.
40: ROC Curves.
41: Role of Statistics.
42: Role of Statistics in Advancing Quantitative Education.
43: Role of Statistics: Developing Country Perspective.
44: Rubin Causal Model.
45: Saddlepoint Approximations.
46: Sample Size Determination.
47: Sample Survey Methods.
48: Sampling Algorithms.
49: Sampling Distribution.
50: Sampling From Finite Populations.
51: Sampling Problems for Stochastic Processes.
52: Scales of Measurement.
53: Scales of Measurement and Choice of Statistical Methods.
54: Seasonal Integration and Cointegration in Economic Time Series.
55: Seasonality.
56: Selection of Appropriate Statistical Methods in Developing Countries.
57: Semiparametric Regression Models.
58: Semi-Variance in Finance.
59: Sensitivity Analysis.
60: Sensometrics.
61: Sequential Probability Ratio Test.
62: Sequential Ranks.
63: Sequential Sampling.
64: Sex Ratio at Birth.
65: Sign Test.
66: Significance Testing: An Overview.
67: Significance Tests, History and Logic of.
68: Significance Tests: A Critique.
69: Simes' Test in Multiple Testing.
70: Simple Linear Regression.
71: Simple Random Sample.
72: Simpson's Paradox.
73: Simulation Based Bayes Procedures for Model Structures with Non-Elliptical Posteriors.
74: Singular Spectrum Analysis for Time Series.
75: SIPOC and COPIS: Business Flow – Business Optimization Connection in a Six Sigma Context.
76: Six Sigma.
77: Skewness.
78: Skew-Normal Distribution.
79: Skew-Symmetric Families of Distributions.
80: Small Area Estimation.
81: Smoothing Splines.
82: Smoothing Techniques.
83: Social Network Analysis.
84: Social Statistics.
85: Sociology, Statistics in.
86: Spatial Point Pattern.
87: Spatial Statistics.
88: Spectral Analysis.
89: Sport, Statistics in.
90: Spreadsheets in Statistics.
91: Spurious Correlation.
92: St. Petersburg Paradox.
93: Standard Deviation.
94: Statistical Analysis of Drug Release Data Within the Pharmaceutical Sciences.
95: Statistical Analysis of Longitudinal and Correlated Data.
96: Statistical Approaches to Protecting Confidentiality in Public Use Data.
97: Statistical Aspects of Hurricane Modeling and Forecasting.
98: Statistical Consulting.
99: Statistical Design of Experiments (DOE).
100: Statistical Distributions: An Overview.
101: Statistical Ecology.
102: Statistical Estimation of Actuarial Risk Measures for Heavy-Tailed Claim Amounts.
103: Statistical Evidence.
104: Statistical Fallacies.
105: Statistical Fallacies: Misconceptions, and Myths.
106: Statistical Genetics.
107: Statistical Inference.
108: Statistical Inference for Quantum Systems.
109: Statistical Inference for Stochastic Processes.
110: Statistical Inference in Ecology.
111: Statistical Inference: An Overview.
112: Statistical Literacy, Reasoning, and Thinking.
113: Statistical Methods for Non-Precise Data.
114: Statistical Methods in Epidemiology.
115: Statistical Modeling of Financial Markets.
116: Statistical Modelling in Market Research.
117: Statistical Natural Language Processing.
118: Statistical Pattern Recognition Principles.
119: Statistical Publications, History of.
120: Statistical Quality Control.
121: Statistical Quality Control: Recent Advances.
122: Statistical Signal Processing.
123: Statistical Significance.
124: Statistical Software: An Overview.
125: Statistical View of Information Theory.
126: Statistics and Climate Change.
127: Statistics and Gambling.
128: Statistics and the Law.
129: Statistics Education.
130: Statistics of Extremes.
131: Statistics on Ranked Lists.
132: Statistics Targeted Clinical Trials Stratified and Personalized Medicines.
133: Statistics, History of.
134: Statistics: An Overview.
135: Statistics: Controversies in Practice.
136: Statistics: Nelder's View.
137: Stem-and-Leaf Plot.
138: Step-Stress Accelerated Life Tests.
139: Stochastic Difference Equations and Applications.
140: Stochastic Differential Equations.
141: Stochastic Global Optimization.
142: Stochastic Modeling, Recent Advances in.
143: Stochastic Modeling Analysis and Applications.
144: Stochastic Models of Transport Processes.
145: Stochastic Processes.
146: Stochastic Processes: Applications in Finance and Insurance.
147: Stochastic Processes: Classification.
148: Stratified Sampling.
149: Strong Approximations in Probability and Statistics.
150: Structural Equation Models.
151: Structural Time Series Models.
152: Student's t-Distribution.
153: Student's t-Tests.
154: Sturges' and Scott's Rules.
155: Sufficient Statistical Information.
156: Sufficient Statistics.
157: Summarizing Data with Boxplots.
158: Superpopulation Models in Survey Sampling.
159: Surveillance.
160: Survival Data.
161: Target Estimation: A New Approach to Parametric Estimation.
162: Telephone Sampling: Frames and Selection Techniques.
163: Testing Exponentiality of Distribution.
164: Testing Variance Components in Mixed Linear Models.
165: Tests for Discriminating Separate or Non-Nested Models.
166: Tests for Homogeneity of Variance.
167: Tests of Fit Based on The Empirical Distribution Function.
168: Tests of Independence.
169: Time Series.
170: Time Series Models to Determine the Death Rate of a Given Disease.
171: Time Series Regression.
172: Total Survey Error.
173: Tourism Statistics.
174: Trend Estimation.
175: Two-Stage Least Squares.
176: Unbiased Estimators and Their Applications.
177: Uniform Distribution in Statistics.
178: Uniform Experimental Design.
179: Uniform Random Number Generators.
180: Univariate Discrete Distributions: An Overview.
181: U-Statistics.
182: Validity of Scales.
183: Variables.
184: Variance.
185: Variation for Categorical Variables.
186: Vector Autoregressive Models.
187: Weak Convergence of Probability Measures.
188: Weibull Distribution.
189: Weighted Correlation.
190: Weighted U-Statistics.
191: Wilcoxon–Mann–Whitney Test.
192: Wilcoxon-Signed-Rank Test.
List of Entries.