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Numerical issues in statistical computing for the social scientist [[electronic resource] /] / Micah Altman, Jeff Gill, Michael P. McDonald
| Numerical issues in statistical computing for the social scientist [[electronic resource] /] / Micah Altman, Jeff Gill, Michael P. McDonald |
| Autore | Altman Micah |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (348 p.) |
| Disciplina | 519.5 |
| Altri autori (Persone) |
GillJeff
McDonaldMichael <1967-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Statistics - Data processing
Social sciences - Statistical methods - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-34479-2
9786610344796 0-470-30664-5 0-471-47574-2 0-471-47576-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Numerical Issues in Statistical Computing for the Social Scientist; Contents; Preface; 1 Introduction: Consequences of Numerical Inaccuracy; 1.1 Importance of Understanding Computational Statistics; 1.2 Brief History: Duhem to the Twenty-First Century; 1.3 Motivating Example: Rare Events Counts Models; 1.4 Preview of Findings; 2 Sources of Inaccuracy in Statistical Computation; 2.1 Introduction; 2.1.1 Revealing Example: Computing the Coefficient Standard Deviation; 2.1.2 Some Preliminary Conclusions; 2.2 Fundamental Theoretical Concepts; 2.2.1 Accuracy and Precision
2.2.2 Problems, Algorithms, and Implementations2.3 Accuracy and Correct Inference; 2.3.1 Brief Digression: Why Statistical Inference Is Harder in Practice Than It Appears; 2.4 Sources of Implementation Errors; 2.4.1 Bugs, Errors, and Annoyances; 2.4.2 Computer Arithmetic; 2.5 Algorithmic Limitations; 2.5.1 Randomized Algorithms; 2.5.2 Approximation Algorithms for Statistical Functions; 2.5.3 Heuristic Algorithms for Random Number Generation; 2.5.4 Local Search Algorithms; 2.6 Summary; 3 Evaluating Statistical Software; 3.1 Introduction; 3.1.1 Strategies for Evaluating Accuracy 3.1.2 Conditioning3.2 Benchmarks for Statistical Packages; 3.2.1 NIST Statistical Reference Datasets; 3.2.2 Benchmarking Nonlinear Problems with StRD; 3.2.3 Analyzing StRD Test Results; 3.2.4 Empirical Tests of Pseudo-Random Number Generation; 3.2.5 Tests of Distribution Functions; 3.2.6 Testing the Accuracy of Data Input and Output; 3.3 General Features Supporting Accurate and Reproducible Results; 3.4 Comparison of Some Popular Statistical Packages; 3.5 Reproduction of Research; 3.6 Choosing a Statistical Package; 4 Robust Inference; 4.1 Introduction; 4.2 Some Clarification of Terminology 4.3 Sensitivity Tests4.3.1 Sensitivity to Alternative Implementations and Algorithms; 4.3.2 Perturbation Tests; 4.3.3 Tests of Global Optimality; 4.4 Obtaining More Accurate Results; 4.4.1 High-Precision Mathematical Libraries; 4.4.2 Increasing the Precision of Intermediate Calculations; 4.4.3 Selecting Optimization Methods; 4.5 Inference for Computationally Difficult Problems; 4.5.1 Obtaining Confidence Intervals with Ill-Behaved Functions; 4.5.2 Interpreting Results in the Presence of Multiple Modes; 4.5.3 Inference in the Presence of Instability 5 Numerical Issues in Markov Chain Monte Carlo Estimation5.1 Introduction; 5.2 Background and History; 5.3 Essential Markov Chain Theory; 5.3.1 Measure and Probability Preliminaries; 5.3.2 Markov Chain Properties; 5.3.3 The Final Word (Sort of); 5.4 Mechanics of Common MCMC Algorithms; 5.4.1 Metropolis-Hastings Algorithm; 5.4.2 Hit-and-Run Algorithm; 5.4.3 Gibbs Sampler; 5.5 Role of Random Number Generation; 5.5.1 Periodicity of Generators and MCMC Effects; 5.5.2 Periodicity and Convergence; 5.5.3 Example: The Slice Sampler; 5.5.4 Evaluating WinBUGS; 5.6 Absorbing State Problem 5.7 Regular Monte Carlo Simulation |
| Record Nr. | UNINA-9910143219303321 |
Altman Micah
|
||
| Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Numerical issues in statistical computing for the social scientist [[electronic resource] /] / Micah Altman, Jeff Gill, Michael P. McDonald
| Numerical issues in statistical computing for the social scientist [[electronic resource] /] / Micah Altman, Jeff Gill, Michael P. McDonald |
| Autore | Altman Micah |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (348 p.) |
| Disciplina | 519.5 |
| Altri autori (Persone) |
GillJeff
McDonaldMichael <1967-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Statistics - Data processing
Social sciences - Statistical methods - Data processing |
| ISBN |
1-280-34479-2
9786610344796 0-470-30664-5 0-471-47574-2 0-471-47576-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Numerical Issues in Statistical Computing for the Social Scientist; Contents; Preface; 1 Introduction: Consequences of Numerical Inaccuracy; 1.1 Importance of Understanding Computational Statistics; 1.2 Brief History: Duhem to the Twenty-First Century; 1.3 Motivating Example: Rare Events Counts Models; 1.4 Preview of Findings; 2 Sources of Inaccuracy in Statistical Computation; 2.1 Introduction; 2.1.1 Revealing Example: Computing the Coefficient Standard Deviation; 2.1.2 Some Preliminary Conclusions; 2.2 Fundamental Theoretical Concepts; 2.2.1 Accuracy and Precision
2.2.2 Problems, Algorithms, and Implementations2.3 Accuracy and Correct Inference; 2.3.1 Brief Digression: Why Statistical Inference Is Harder in Practice Than It Appears; 2.4 Sources of Implementation Errors; 2.4.1 Bugs, Errors, and Annoyances; 2.4.2 Computer Arithmetic; 2.5 Algorithmic Limitations; 2.5.1 Randomized Algorithms; 2.5.2 Approximation Algorithms for Statistical Functions; 2.5.3 Heuristic Algorithms for Random Number Generation; 2.5.4 Local Search Algorithms; 2.6 Summary; 3 Evaluating Statistical Software; 3.1 Introduction; 3.1.1 Strategies for Evaluating Accuracy 3.1.2 Conditioning3.2 Benchmarks for Statistical Packages; 3.2.1 NIST Statistical Reference Datasets; 3.2.2 Benchmarking Nonlinear Problems with StRD; 3.2.3 Analyzing StRD Test Results; 3.2.4 Empirical Tests of Pseudo-Random Number Generation; 3.2.5 Tests of Distribution Functions; 3.2.6 Testing the Accuracy of Data Input and Output; 3.3 General Features Supporting Accurate and Reproducible Results; 3.4 Comparison of Some Popular Statistical Packages; 3.5 Reproduction of Research; 3.6 Choosing a Statistical Package; 4 Robust Inference; 4.1 Introduction; 4.2 Some Clarification of Terminology 4.3 Sensitivity Tests4.3.1 Sensitivity to Alternative Implementations and Algorithms; 4.3.2 Perturbation Tests; 4.3.3 Tests of Global Optimality; 4.4 Obtaining More Accurate Results; 4.4.1 High-Precision Mathematical Libraries; 4.4.2 Increasing the Precision of Intermediate Calculations; 4.4.3 Selecting Optimization Methods; 4.5 Inference for Computationally Difficult Problems; 4.5.1 Obtaining Confidence Intervals with Ill-Behaved Functions; 4.5.2 Interpreting Results in the Presence of Multiple Modes; 4.5.3 Inference in the Presence of Instability 5 Numerical Issues in Markov Chain Monte Carlo Estimation5.1 Introduction; 5.2 Background and History; 5.3 Essential Markov Chain Theory; 5.3.1 Measure and Probability Preliminaries; 5.3.2 Markov Chain Properties; 5.3.3 The Final Word (Sort of); 5.4 Mechanics of Common MCMC Algorithms; 5.4.1 Metropolis-Hastings Algorithm; 5.4.2 Hit-and-Run Algorithm; 5.4.3 Gibbs Sampler; 5.5 Role of Random Number Generation; 5.5.1 Periodicity of Generators and MCMC Effects; 5.5.2 Periodicity and Convergence; 5.5.3 Example: The Slice Sampler; 5.5.4 Evaluating WinBUGS; 5.6 Absorbing State Problem 5.7 Regular Monte Carlo Simulation |
| Record Nr. | UNINA-9910830158403321 |
|
Altman Micah
|
||
| Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Numerical issues in statistical computing for the social scientist / / Micah Altman, Jeff Gill, Michael P. McDonald
| Numerical issues in statistical computing for the social scientist / / Micah Altman, Jeff Gill, Michael P. McDonald |
| Autore | Altman Micah |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (348 p.) |
| Disciplina | 519.5 |
| Altri autori (Persone) |
GillJeff
McDonaldMichael <1967-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Statistics - Data processing
Social sciences - Statistical methods - Data processing |
| ISBN |
1-280-34479-2
9786610344796 0-470-30664-5 0-471-47574-2 0-471-47576-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Numerical Issues in Statistical Computing for the Social Scientist; Contents; Preface; 1 Introduction: Consequences of Numerical Inaccuracy; 1.1 Importance of Understanding Computational Statistics; 1.2 Brief History: Duhem to the Twenty-First Century; 1.3 Motivating Example: Rare Events Counts Models; 1.4 Preview of Findings; 2 Sources of Inaccuracy in Statistical Computation; 2.1 Introduction; 2.1.1 Revealing Example: Computing the Coefficient Standard Deviation; 2.1.2 Some Preliminary Conclusions; 2.2 Fundamental Theoretical Concepts; 2.2.1 Accuracy and Precision
2.2.2 Problems, Algorithms, and Implementations2.3 Accuracy and Correct Inference; 2.3.1 Brief Digression: Why Statistical Inference Is Harder in Practice Than It Appears; 2.4 Sources of Implementation Errors; 2.4.1 Bugs, Errors, and Annoyances; 2.4.2 Computer Arithmetic; 2.5 Algorithmic Limitations; 2.5.1 Randomized Algorithms; 2.5.2 Approximation Algorithms for Statistical Functions; 2.5.3 Heuristic Algorithms for Random Number Generation; 2.5.4 Local Search Algorithms; 2.6 Summary; 3 Evaluating Statistical Software; 3.1 Introduction; 3.1.1 Strategies for Evaluating Accuracy 3.1.2 Conditioning3.2 Benchmarks for Statistical Packages; 3.2.1 NIST Statistical Reference Datasets; 3.2.2 Benchmarking Nonlinear Problems with StRD; 3.2.3 Analyzing StRD Test Results; 3.2.4 Empirical Tests of Pseudo-Random Number Generation; 3.2.5 Tests of Distribution Functions; 3.2.6 Testing the Accuracy of Data Input and Output; 3.3 General Features Supporting Accurate and Reproducible Results; 3.4 Comparison of Some Popular Statistical Packages; 3.5 Reproduction of Research; 3.6 Choosing a Statistical Package; 4 Robust Inference; 4.1 Introduction; 4.2 Some Clarification of Terminology 4.3 Sensitivity Tests4.3.1 Sensitivity to Alternative Implementations and Algorithms; 4.3.2 Perturbation Tests; 4.3.3 Tests of Global Optimality; 4.4 Obtaining More Accurate Results; 4.4.1 High-Precision Mathematical Libraries; 4.4.2 Increasing the Precision of Intermediate Calculations; 4.4.3 Selecting Optimization Methods; 4.5 Inference for Computationally Difficult Problems; 4.5.1 Obtaining Confidence Intervals with Ill-Behaved Functions; 4.5.2 Interpreting Results in the Presence of Multiple Modes; 4.5.3 Inference in the Presence of Instability 5 Numerical Issues in Markov Chain Monte Carlo Estimation5.1 Introduction; 5.2 Background and History; 5.3 Essential Markov Chain Theory; 5.3.1 Measure and Probability Preliminaries; 5.3.2 Markov Chain Properties; 5.3.3 The Final Word (Sort of); 5.4 Mechanics of Common MCMC Algorithms; 5.4.1 Metropolis-Hastings Algorithm; 5.4.2 Hit-and-Run Algorithm; 5.4.3 Gibbs Sampler; 5.5 Role of Random Number Generation; 5.5.1 Periodicity of Generators and MCMC Effects; 5.5.2 Periodicity and Convergence; 5.5.3 Example: The Slice Sampler; 5.5.4 Evaluating WinBUGS; 5.6 Absorbing State Problem 5.7 Regular Monte Carlo Simulation |
| Record Nr. | UNINA-9910876853803321 |
|
Altman Micah
|
||
| Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The Public Mapping Project : How Public Participation Can Revolutionize Redistricting / / Michael P. McDonald and Micah Altman
| The Public Mapping Project : How Public Participation Can Revolutionize Redistricting / / Michael P. McDonald and Micah Altman |
| Autore | Altman Micah |
| Pubbl/distr/stampa | Ithaca : , : Cornell Selects, an imprint of Cornell University Press, , 2018 |
| Descrizione fisica | 1 online resource : illustrations (black and white, and colour), map (colour) |
| Disciplina | 328.73/07345 |
| Collana | Brown Democracy Medal |
| Soggetto topico |
Digital mapping - United States
Election districts - United States |
| ISBN | 1-5017-3855-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- A history of public mapping -- Planning for public mapping -- DistrictBuilder -- Public mapping and redistricting reform. |
| Record Nr. | UNINA-9910296441003321 |
|
Altman Micah
|
||
| Ithaca : , : Cornell Selects, an imprint of Cornell University Press, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||