Discrete functional data analysis Masahiro Mizuta 29. In this paper we focus on this descriptive aspect. Jafari, Andrew Nesbit, Emmanuel Vincent, Beiming Wang 10. Whether computed on test data or through cross-validation, this error rate is suited for classification purposes. Special attention is devoted to computational aspects. Use of latent class regression models with a random intercept to remove the effects of the overall response rating level Jay Magidson, Jeroen K. Exploratory modelling analysis: visualizing the value of variables Antony Unwin 18.
Operator related to a data matrix: a survey Yves Escoufier 23. Musical audio analysis using sparse representations Mark D. Robust correspondence recognition for computer vision Radim Šára 11. Image Analysis and Signal Processing 8. Genetic algorithms for building double threshold generalized autoregressive conditional heteroscedastic models of time series Roberto Baragona, Francesco Battaglia 36. A robust linear grouping algorithm Greet Pison, Stefan Aelst, Ruben H. We consider the deviance as a goodness-of-fit statistic that attempts to measure how well the tree is at reproducing the conditional distribution of the response variable for each possible profile rather than the individual response value for each case and we discuss various statistical tests that can be derived from them.
Tying up the loose ends in simple, multiple, joint correspondence analysis Michael Greenacre 14. Challenges concerning web data mining Wolfgang Gaul 33. Issues of robustness and high dimensionality in cluster analysis Kaye Basford, Geoff McLachlan, Richard Bean 2. Visualization in comparative music research Petri Toiviainen, Tuomas Eerola 17. Abdallah, Thomas Blumensath, Maria G. Visiting near-optimal solutions using local search algorithms Sheldon H.
Latent class model with two latent variables for analysis of count data Kazunori Yamaguchi, Naoko Sakurai, Michiko Watanabe Part V. Geospatial distribution of alcohol-related violence in Northern Virginia Yasmin H. Factor interval data analysis and its application Huiwen Wang, Henry M. Estimation procedures for the false discovery rate: a systematic comparison for microarray data Michael G. Robust classification with categorical variables Andrea Cerioli, Marco Riani, Anthony C. The proceedings should appeal to anyone working in statistics and using computers, whether in universities, industrial companies, government agencies, research institutes or as software developers Invited papers.
Bootstrap methods for measuring classification uncertainty in latent class analysis José G. For example, the error rate is not representative of the quality of the description provided. Density estimation from streaming data using wavelets Edward J. Identifying excessively rounded or truncated data Kevin H. Subset selection algorithm based on mutual information Moon Y. Nonparametric evaluation of matching noise Pier Luigi Conti, Daniela Marella, Mauro Scanu 37.
. Blind superresolution Filip Šroubek, Gabriel Cristóbal, Jan Flusser 12. Computing and using the deviance with classification trees Gilbert Ritschard 6. Symbolic data analysis: what is it? We claim that it is, however, a partial indicator only of the quality of the knowledge provided by trees and that there is a need for additional indicators. Reducing conservatism of exact small-sample methods of inference for discrete data Alan Agresti, Anna Gottard 20. Statistical inference and data mining: false discoveries control Stéphane Lallich, Olivier Teytaud, Elie Prudhomme 26.
Parameterization and estimation of path models for categorical data Tamás Rudas, Wicher Bergsma, Renáta Németh 31. Published in Rizzi, Alfredo and Vichi, Maurizio. Keywords — — — — Identifiers. The content of the book covers all aspects of this link, from the development and implementation of new statistical ideas to user experiences and software evaluation. Table of contents Part I. . .
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