Statistical Methods in Software Engineering by Nozer D Singpurwalla
This preface pertains to three issues that we would like to bring to the attention of the readers: our objectives, our intended audience, and the nature of the material. We have in mind several objectives. The first is to establish a framework for dealing with uncertainties in software engineering, and for using quantitative measures for decision making in this context. The second is to bring into perspective the large body of work having statistical content that is relevant to software engineering, which may not have appeared in the traditional outlets devoted to it. Connected with this second objective is a desire to streamline and organize our own thinking and work in this area. Our third objective is to provide a platform that facilitates an interface between computer scientists and statisticians to address a class of problems in computer science. It appears that such an interface is necessary to provide the needed synergism for solving some difficult problems that the subject poses. Our final objective is to serve as an agent for stimulating more cross-disciplinary research in computer science and statistics. To what extent the material here will meet our objectives can only be assessed with the passage of time. Our intended audience is computer scientists, software engineers, and reliability analysts, who have some exposure to probability and statistics. Applied statisticians interested in reliability problems are also a segment of our intended audience.-
The Elements of Statistical Learning
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Dragons of Winter Night
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Functional Data Analysis
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Time Series: Theory and Methods
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Modeling Discrete Time-to-Event Data
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Targeted Learning
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Models for Discrete Longitudinal Data
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Regression Modeling Strategies
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Targeted Learning in Data Science
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An Introduction to Sequential Monte Carlo
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Modern Multidimensional Scaling
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Correlation Theory of Stationary and Related Random Functions
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Mathematical Statistics
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Breakthroughs in Statistics
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Annotated Readings in the History of Statistics
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Statistical Models Based on Counting Processes
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Hidden Markov Processes and Adaptive Filtering
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Design of Observational Studies
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Chaos: A Statistical Perspective
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A Comparison of the Bayesian and Frequentist Approaches to Estimation
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Smoothing Spline ANOVA Models
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Analysis of Neural Data
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Finite Mixture and Markov Switching Models
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The Gini Methodology
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Ten Projects in Applied Statistics
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Growth Curve Models and Statistical Diagnostics
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
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Markov Bases in Algebraic Statistics
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Data
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A Course on Point Processes
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Shrinkage Estimation
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Theory of Statistics
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Bayesian and Frequentist Regression Methods
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A Statistical Model
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Prediction Theory for Finite Populations
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Tools for Statistical Inference
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Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series
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ARMA Model Identification
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Statistical Design and Analysis for Intercropping Experiments
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Approximate Distributions of Order Statistics
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Robust Asymptotic Statistics
| SKU | Unavailable |
| ISBN 13 | 9781461268208 |
| ISBN 10 | 1461268206 |
| Title | Statistical Methods in Software Engineering |
| Author | Nozer D Singpurwalla |
| Series | Springer Series In Statistics |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer-Verlag New York Inc. |
| Year published | 2012-09-27 |
| Number of pages | 297 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |