Data analysis and approximate models : model choice, location-scale, analysis of variance, nonparametic regression and image analysis /: model choice, location-scale, analysis of variance, nonparametic regression and image analysis. (2014)

• Record Type: Book
• Further Information: Note: Patrick Laurie Davies.
• Authors: Davies, Patrick Laurie
• Contents: Introduction; Introduction; Approximate Models; Notation; Two Modes of Statistical Analysis; Towards One Mode of Analysis; Approximation, Randomness, Chaos, Determinism; Approximation A Concept of Approximation ; Approximation; Approximating a Data Set by a Model; Approximation Regions; Functionals and Equivariance; Regularization and Optimality; Metrics and Discrepancies; Strong and Weak Topologies; On Being (almost) Honest; Simulations and Tables; Degree of Approximation and p-values; Scales; Stability of Analysis; The Choice of En (α, P ); Independence; Procedures, Approximation and Vagueness Discrete Models ; The Empirical Density; Metrics and Discrepancies; The Total Variation Metric; The Kullback-Leibler and Chi-Squared Discrepancies; The Po (λ ) Model; The b(k, p ) and nb(k, p ) Models; The Flying Bomb Data; The Student Study Times Data Outliers ; Outliers, Data Analysis and Models; Breakdown Points and Equivariance; Identifying Outliers and Breakdown; Outliers in Multivariate Data; Outliers in Linear Regression; Outliers in Structured Data The Location-Scale Problem ; Robustness; Efficiency and Regularization; M -functionals; Approximation Intervals, Quantiles and Bootstrapping; Stigler’s Comparison of Eleven Location Functionals Based on Historical Data Sets; An Attempt at an Automatic Procedure; Multidimensional M -functionals The Analysis of Variance ; The One-Way Table; The Two-Way Table; The Three-Way and Higher Tables; Interactions in the Presence of Noise; Examples Nonparametric Regression: Location; A Definition of Approximation; Regularization; Rates of Convergence and Approximation Bands; Choosing Smoothing Parameters; Joint Approximation of Two or More Samples; Inverse Problems; Heterogeneous Noise Nonparametric Regression: Scale; The Standard Model and a Concept of Approximation; Piecewise Constant Scale and Local Approximation; GARCH Segmentation; The Taut String and Scale; Smooth Scale Functions; Comparison of the Four Methods; Location and Scale Image Analysis; Two and Higher Dimensions; The Approximation Region; Linear Programming and Related Methods; Choosing Smoothing Parameters Nonparametric Densities ; Introduction; Approximation Regions and Regularization; The Taut String Strategy for Densities; Smoothing the Taut String Approximation A Critique of Statistics ; Likelihood; Bayesian Statistics; Sufficient Statistics; Efficiency; Asymptotics; Model Choice; What Can Actually Be Estimated? Bibliography Index
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2014
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 519.5; Probabilities -- Philosophy; Approximation theory
• Languages: English
• ISBNs: 9781482215878
• Related ISBNs: 9781482215861
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; item not viewed.
• 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.