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武汉理工大学汽车营销与策划英文课件chapter8 Data Analysis。
Optimal rates of convergence for persistence diagrams in Topological Data Analysis
Optimal rates convergence persistence diagrams Topological Data Analysis
2013/6/14
Computational topology has recently known an important development toward data analysis, giving birth to the field of topological data analysis. Topological persistence, or persistent homology, appear...
Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
Coordinate descent counts data overdispersion regularized likelihood sparse group penalty
2013/6/14
With the development of next generation sequencing technology, researchers have now been able to study the microbiome composition using direct sequencing, whose output are bacterial taxa counts for ea...
Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
Coordinate descent counts data overdispersion regularized likelihood sparse group penalty
2013/6/14
With the development of next generation sequencing technology, researchers have now been able to study the microbiome composition using direct sequencing, whose output are bacterial taxa counts for ea...
Tensor Decompositions: A New Concept in Brain Data Analysis?
Multilinear BSS linked multiway BSS/ICA tensor factorizations and de-compositions constrained Tucker and CP models PenalizedTensor Decompositions (PTD) feature extraction classification multiway PLS and CCA
2013/6/14
Matrix factorizations and their extensions to tensor factorizations and decompositions have become prominent techniques for linear and multilinear blind source separation (BSS), especially multiway In...
Identification of Signal, Noise, and Indistinguishable Subsets in High-Dimensional Data Analysis
Two-Level Thresholding Signal detection False positive control False negative control Multiple testing Variable screening
2013/6/13
Motivated by applications in high-dimensional data analysis where strong signals often stand out easily and weak ones may be indistinguishable from the noise, we develop a statistical framework to pro...
Object Oriented Data Analysis of Cell-Well Structured Data
data objects cell con uence bright
2013/4/28
Object oriented data analysis (OODA) aims at statistically analyzing populations of complicated objects. This paper is motivated by a study of cell images in cell culture biology, which highlights a c...
Data Mining and Exploratory Data Analysis for the Evaluation of Job Satisfaction
Customer Relationship Management Relationship Value Management Job Satisfaction Social Enterprise Data Mining, Ordered Multiple Correspondence Analysis
2013/2/23
In this paper we face off the relationship value management which is a theme in the relationship marketing literature gaining increasing attention in the last decade. The main aim of this study is to ...
Statistical methods of SNP data analysis with applications
Genetic data statistical analysis multifactor dimensiona-lity reduction
2011/7/7
Various statistical methods important for genetic analysis are considered and developed. Namely, we concentrate on the multifactor dimensionality reduction, logic regression, random forests and stocha...
Baby Morse Theory in Data Analysis
Topology Morse theory persistence inference signal detection
2011/6/17
A methodology is proposed for inferring the topology underlying point cloud
data. The approach employs basic elements of Morse Theory, and is capable
of producing not only a point estimate of variou...
Algorithmic and Statistical Perspectives on Large-Scale Data Analysis
Algorithmic Statistical Perspectives Large-Scale Data Analysis
2010/10/19
In recent years, ideas from statistics and scientific computing have begun to interact in increasingly sophisticated and fruitful ways with ideas from computer science and the theory of algorithms to...
On computational tools for Bayesian data analysis
Bayesian inference Monte Carlo methods MCMC algorithms Approximate Bayesian Computation techniques adaptivity
2010/3/10
While the previous chapter (Robert and Rousseau,
2010) addressed the foundational aspects of Bayesian
analysis, the current chapter details its practical aspects
through a review of the computation...
On Bayesian Data Analysis
Bayesian inference Bayes model choice foundations testing non-informative prior Bayesiannonparametrics Bayes factor
2010/3/9
This introduction to Bayesian statistics presents the
main concepts as well as the principal reasons advocated
in favour of a Bayesian modelling. We cover
the various approaches to prior determinat...
Robustness and accuracy of methods for high dimensional data analysis based on Student's t statistic
Bootstrap central limit theorem classication dimension reduction higher criticism large deviation probability
2010/3/9
Student's t statistic is nding applications today that were never envisaged
when it was introduced more than a century ago. Many of these applications
rely on properties, for example robustness aga...
Health worker densities and immunization coverage in Turkey: a panel data analysis
health worker densities immunization coverage Turkey panel data analysis
2009/9/27
We find evidence of relationships between HRH densities and vaccination rates even at Turkey's relatively elevated levels of each. At the same time, variations in results between different empirical m...