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CSDA
2008
128views more  CSDA 2008»
13 years 5 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
CSDA
2008
91views more  CSDA 2008»
13 years 5 months ago
Model-based clustering for longitudinal data
A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hier...
Rolando De la Cruz-Mesía, Fernando A. Quint...
CSDA
2008
84views more  CSDA 2008»
13 years 5 months ago
Bayesian spatial prediction of the site index in the study of the Missouri Ozark Forest Ecosystem Project
This paper presents a Bayesian spatial method for analysing the site index data from the Missouri Ozark Forest Ecosystem Project (MOFEP). Based on ecological background and availa...
Xiaoqian Sun, Zhuoqiong He, John Kabrick
CSDA
2008
122views more  CSDA 2008»
13 years 5 months ago
Bayesian inference for nonlinear multivariate diffusion models observed with error
Diffusion processes governed by stochastic differential equations (SDEs) are a well established tool for modelling continuous time data from a wide range of areas. Consequently, t...
Andrew Golightly, Darren J. Wilkinson
CSDA
2008
54views more  CSDA 2008»
13 years 5 months ago
Faster ARMA maximum likelihood estimation
A. I. McLeod, Y. Zhang
CSDA
2008
95views more  CSDA 2008»
13 years 5 months ago
On the hazard function of Birnbaum-Saunders distribution and associated inference
In this paper, we discuss the shape of the hazard function of Birnbaum
Debasis Kundu, Nandini Kannan, N. Balakrishnan
CSDA
2008
64views more  CSDA 2008»
13 years 5 months ago
Sequential calibration of options
Erik Lindström, Jonas Ströjby, Mats Brod...
CSDA
2008
158views more  CSDA 2008»
13 years 5 months ago
Outlier identification in high dimensions
A computationally fast procedure for identifying outliers is presented, that is particularly effective in high dimensions. This algorithm utilizes simple properties of principal c...
Peter Filzmoser, Ricardo A. Maronna, Mark Werner
CSDA
2008
154views more  CSDA 2008»
13 years 5 months ago
Independent factor discriminant analysis
In the general classification context the recourse to the so-called Bayes decision rule requires to estimate the class conditional probability density functions. In this paper we p...
Angela Montanari, Daniela G. Calò, Cinzia V...