Computational statistics handbook with MATLAB. (2007)

• Record Type: Book
• Further Information: Note: Wendy L. Martinez, Angel R. Martinez.
• Other Names: Martinez, Wendy L; Martinez, Angel R
• Contents: Prefaces ; Introduction ; What Is Computational Statistics?; An Overview of the Book; Probability Concepts ; Introduction; Probability; Conditional Probability and Independence; Expectation; Common Distributions; Sampling Concepts ; Introduction; Sampling Terminology and Concepts; Sampling Distributions; Parameter Estimation; Empirical Distribution Function; Generating Random Variables ; Introduction; General Techniques for Generating Random Variables; Generating Continuous Random Variables; Generating Discrete Random Variables; Exploratory Data Analysis ; Introduction; Exploring Univariate Data; Exploring Bivariate and Trivariate Data; Exploring Multidimensional Data; Finding Structure ; Introduction; Projecting Data; Principal Component Analysis; Projection Pursuit EDA; Independent Component Analysis; Grand Tour; Nonlinear Dimensionality Reduction; Monte Carlo Methods for Inferential Statistics ; Introduction; Classical Inferential Statistics; Monte Carlo Methods for Inferential Statistics; Bootstrap Methods; Data Partitioning ; Introduction; Cross-Validation; Jackknife; Better Bootstrap Confidence Intervals; Jackknife-after-Bootstrap; Probability Density Estimation ; Introduction; Histograms; Kernel Density Estimation; Finite Mixtures; Generating Random Variables; Supervised Learning ; Introduction; Bayes’ Decision Theory; Evaluating the Classifier; Classification Trees; Combining Classifiers; Unsupervised Learning ; Introduction; Measures of Distance; Hierarchical Clustering; K-Means Clustering; Model-Based Clustering; Assessing Cluster Results; Parametric Models ; Introduction; Spline Regression Models; Logistic Regression; Generalized Linear Models; Nonparametric models ; Introduction; Some Smoothing Methods; Kernel Methods; Smoothing Splines; Nonparametric Regression—Other Details; Regression Trees; Additive Models; Markov Chain Monte Carlo Methods ; Introduction; Background; Metropolis–Hastings Algorithms; The Gibbs Sampler; Convergence Monitoring; Spatial Statistics ; Introduction; Visualizing Spatial Point Processes; Exploring First-Order and Second-Order Properties; Modeling Spatial Point Processes; Simulating Spatial Point Processes; Appendix A: Introduction to Matlab ; What Is MATLAB?; Getting Help in MATLAB; File and Workspace Management; Punctuation in MATLAB; Arithmetic Operators; Data Constructs in MATLAB; Script Files and Functions; Control Flow ; Simple Plotting; Contact Information; Appendix B: Projection Pursuit Indexes ; Indexes; MATLAB Source Code; Appendix C: Matlab Statistics Toolbox ; Appendix D: Computational Statistics Toolbox ; Appendix E: Exploratory Data Analysis Toolboxes ; Introduction; EDA Toolbox; EDA GUI Toolbox; Appendix F: Data Sets ; Appendix G: NOTATION ; References ; INDEX ; MATLAB Code, Further Reading, and Exercises appear at the end of each chapter.
• Edition: 2nd ed
• Publisher Details: Place of publication not identified : Chapman and Hall/CRC
• Publication Date: 2007
• Extent: 1 online resource (792 pages), (211 illustrations)
• Subjects: 519.50285; Mathematical statistics -- Data processing
• Languages: English
• ISBNs: 9781420010862; 1420010867
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.