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COMPSTAT : Proceedings in Computational Statistics 14th Symposium held in Utrecht, The Netherlands, 2000

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Table of Contents

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    Book Overview
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    Chapter 1 The broad role of multiple imputation in statistical science
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    Chapter 2 Official Statistics: an estimation strategy for the IT-era
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    Chapter 3 Bayesian model selection methods for nonnested models
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    Chapter 4 Spatio-temporal hierarchical modeling of an infectious disease from (simulated) count data
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    Chapter 5 GBMs: GLMs with bilinear terms
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    Chapter 6 Generalized calibration and application to weighting for non-response
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    Chapter 7 Methodological issues in data mining
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    Chapter 8 Practical data mining in a large utility company
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    Chapter 9 HGLMs for analysis of correlated non-normal data
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    Chapter 10 Bootstrapping impulse responses in VAR analyses
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    Chapter 11 An application of TRAMO-SEATS; model selection and out-of-sample performance. The Swiss CPI series
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    Chapter 12 Spreadsheets as tools for statistical computing and statistics education
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    Chapter 13 An algorithm for deepest multiple regression
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    Chapter 14 Non-proportional hazards models in survival analysis
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    Chapter 15 A spatio-temporal analysis of a field trial
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    Chapter 16 Principal component logistic regression
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    Chapter 17 Sieve bootstrap prediction intervals
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    Chapter 18 Clustering by maximizing a fuzzy classification maximum likelihood criterion
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    Chapter 19 Tree-based algorithms for missing data imputation
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    Chapter 20 MiPy: a system for generating multiple imputations
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    Chapter 21 A linear approximation to the wild bootstrap in specification testing
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    Chapter 22 The size of the largest nonidentifiable outlier as a performance criterion for multivariate outlier identification: the case of high-dimensional data
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    Chapter 23 The influence of data generation and imputation methods on the bias of factor analysis of rating scale data
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    Chapter 24 Model on a population and prediction on another one: a generalized discriminant rule
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    Chapter 25 Disclosure control on multi-way tables by means of the shuttle algorithm: extensions and experiments
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    Chapter 26 An MLE strategy for combining optimally pruned decision trees
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    Chapter 27 Semi-parametric models for data mining
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    Chapter 28 Preliminary estimation of ARFIMA models
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    Chapter 29 A collection of applets for visualizing statistical concepts
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    Chapter 30 Non-parametric regression and density estimation under control of modality
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    Chapter 31 Multivariate approaches for aggregate time series 1
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    Chapter 32 Some space-time models: an application to NO 2 pollution in an urban area
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    Chapter 33 SLICE: generalised software for statistical data editing and imputation
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    Chapter 34 Improved PCB inspection: computational issues
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    Chapter 35 Optimization of the antithetic Gibbs sampler for Gaussian Markov random fields
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    Chapter 36 Computing zonoid trimmed regions of bivariate data sets
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    Chapter 37 Outlier resistant estimators for canonical correlation analysis
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    Chapter 38 Graphical and phase space models for univariate time series
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    Chapter 39 The use of the Tweedie distribution in statistical modelling
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    Chapter 40 Predictive dimension: an alternative definition to embedding dimension
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    Chapter 41 Post-stratification to correct for nonresponse: classification of ZIP code areas
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    Chapter 42 Approximate Bayesian inference for simple mixtures
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    Chapter 43 Correlated INAR(1) process
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    Chapter 44 Confidence regions for stabilized multivariate tests
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    Chapter 45 Comparison of stationary time series using distribution-free methods
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    Chapter 46 Generation of Boolean classification rules
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    Chapter 47 A statistical package based on Pnuts
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    Chapter 48 Generalized regression trees 1
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    Chapter 49 Generalized linear mixed models: An improved estimating procedure
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    Chapter 50 The stochastic dimension in a dynamic GIS
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    Chapter 51 A robust version of principal factor analysis
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    Chapter 52 TESS: system for automatic seasonal adjustment and forecasting of time series
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    Chapter 53 The BADAME project
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    Chapter 54 Improving Statistics Canada’s cell suppression software (CONFID)
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    Chapter 55 The multimedia project MM*STAT for teaching statistics
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    Chapter 56 Projection pursuit approach to robust canonical correlation analysis
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    Chapter 57 A fast algorithm for highly robust regression in data mining
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    Chapter 58 Optimal classification trees
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    Chapter 59 GAM spline algorithms: a direct comparison
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    Chapter 60 Markov Chain Monte Carlo methods for handling missing covariates in longitudinal mixed models
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    Chapter 61 Robust Bayesian classification
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    Chapter 62 Social science measurement by means of item response models
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    Chapter 63 Multivariate DLMs for forecasting financial time series, with application to the management of portfolios
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    Chapter 64 An algorithm for the multivariate Tukey median
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    Chapter 65 Analyzing and synthesizing information from a multiple-study database
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    Chapter 66 Bootstrapping neural discriminant model
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    Chapter 67 An improved algorithm for robust PCA
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    Chapter 68 Applying techniques of dynamic programming to sequential mastery testing
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    Chapter 69 The introduction of formal structure into the processing of statistical summary data
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    Chapter 70 Validation of association rules by interactive mosaic plots
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    Chapter 71 Optimality models for PRAM
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    Chapter 72 Dealing with real ordinal data: recent advances in analyzing tied, censored, and multivariate observations
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    Chapter 73 Testing for differences in location: a comparison of bootstrap methods in the small sample case
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    Chapter 74 Two principal points for location mixtures
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    Chapter 75 Vector splines and other vector smoothers
Overall attention for this book and its chapters
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Title
COMPSTAT : Proceedings in Computational Statistics 14th Symposium held in Utrecht, The Netherlands, 2000
Published by
Physica-Verlag, January 2000
DOI 10.1007/978-3-642-57678-2
ISBNs
978-3-79-081326-5, 978-3-64-257678-2
Authors

Verbyla, A., Lorimer, M., Stevens, R.

Editors

Bethlehem, Jelke G., Heijden, Peter G. M.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 13%
Unknown 7 88%
Readers by discipline Count As %
Unknown 8 100%