Journal of Computational & Graphical Statistics articles from September 2004

Journal of Computational & Graphical Statistics archives from September 2004

Human animation using nonparametric regression.
September 1, 2004... This article describes how to build a nonparametric regression model for the prediction of human motions using motion capture data. The method works by selecting a few similar motions from a database and then averaging them. An appropriate...

Dimension reduction via marginal fourth moments in regression.
September 1, 2004... The conditional mean of the response given the predictors is often of interest in regression problems. The central mean subspace, recently introduced by Cook and Li, allows inference about aspects of the mean function in a largely nonparametric...

Change trees and mutagrams for the visualization of local changes in sequence data.
September 1, 2004... The analysis of local changes in sequence data is of interest for various applications such as the segmentation of DNA and other genetic sequences, or financial data sequences. Patterns of change that can be characterized as local jump change...

Maximum likelihood regression trees.
September 1, 2004... We propose a method of constructing regression trees within the framework of maximum likelihood. It inherits the backward fitting idea of classification and regression trees (CART) but has more rigorous justification. Simulation studies show...

Visualization of multivariate density estimates with level set trees.
September 1, 2004... This article presents a method for visualization of multivariate functions. The method is based on a tree structure--called the level set tree--built from separated parts of level sets of a function. The method is applied for visualization of...

A Haar-Fisz algorithm for Poisson intensity estimation.
September 1, 2004... This article introduces a new method for the estimation of the intensity of an inhomogeneous one-dimensional Poisson process. The Haar-Fisz transformation transforms a vector of binned Poisson counts to approximate normality with variance one....

Wavelet packet methods for the analysis of variance of time series with application to crack widths on the Brunelleschi dome.(Santa Maria del Fiore cathedral )
September 1, 2004... In this article we extend the definition of wavelet variance to wavelet packets. We also adapt Io wavelet packets all iterated cumulative sum of squares algorithm for the location of variance change points. Wavelet packets have greater...

Boosting Diracs for electrophoresis.
September 1, 2004... Electrophoresis is a biochemical process widely used in life sciences and genetics. Recovering information on weights and proportions of molecules from electrophoresis signals may be viewed as a linear inverse problem in the context of a...

A recursive algorithm to restore images based on robust estimation of NSHP autoregressive models.(nonsymmetric half-plane )
September 1, 2004... The objective of this article is to present a new image restoration algorithm. First, each pixel in the image is classified into k categories. Then we assume that the gray levels in each category follow a nonsymmetric half-plane (NSHP)...

Benchmark estimation for Markov chain Monte Carlo samples.
September 1, 2004... While studying various features of the posterior distribution of a vector-valued parameter using an MCMC sample, a subsample is often all that is available for analysis. The goal of benchmark estimation is to use the best available information,...

Monte Carlo maximum likelihood in model-based geostatistics.
September 1, 2004... When using a model-based approach to geostatistical problems, often, due to the complexity of the models, inference relies on Markov chain Monte Carlo methods. This article focuses on the generalized linear spatial models, and demonstrates that...

Investigating the use of the variogram for lattice data.
September 1, 2004... The standard tool used in the analysis of geostatistical data is the variogram. When the variogram is applied to lattice data, most commonly the data associated with each region are assumed to have been observed and arbitrarily assigned at the...

A second-order approximation to the log-likelihood surface for mixture models, with application to the EM algorithm.
September 1, 2004... This article considers a new approximation to the log-likelihood surface in mixture models. This approximation is based on both the mean and variance of the full-data log likelihood over imputations of assignments of observations to components....