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Relationships between eigen and complex network techniques for the statistical analysis of climate data
eigen complex network techniques statistical analysis climate data
2013/6/17
Eigen techniques such as empirical orthogonal function (EOF) or coupled pattern (CP) analysis have been frequently used for detecting patterns in multivariate climatological data sets. Recently, stati...
A Scoring System for Continuous Glucose Monitor Data
Scoring System Continuous Glucose Monitor Data
2013/6/14
As continuous glucose monitors (CGMs) are used increasingly by diabetic patients, new and intuitive tools are needed to help patients and their physicians use these streams of data to improve blood gl...
The student's dilemma: ranking and improving prediction at test time without access to training data
The student's dilemma ranking improving prediction test time without access training data
2013/4/27
The standard approach to rank the performance of several classifiers for a given classification problem is via an independent labeled validation dataset. However, in various applications only unlabele...
Modelling interactions in high-dimensional data with Backtracking
Backtracking interactions Lasso parallel computing path algorithm.
2012/9/17
We study the problem of high-dimensional regression when there may be interacting vari-ables. We introduce a new idea called Backtracking, that can be incorporated into many existing high-dimensional ...
Changepoint detection for high-dimensional time series with missing data
Change point detection high-dimensional time series missing data
2012/9/17
This paper describes a novel approach to changepoint detection when the observed high-dimensional data may have missing elements. The performance of classical methods for changepoint detection typical...
Graph-Based Tests for Two-Sample Comparisons of Categorical Data
Two-sample tests categorical data discrete data minimum spanning trees graph-based tests contingency table.
2012/9/18
We study the problem of two-sample comparisons with categorical data when the contingency table is sparsely populated. Classical methods, such as the Pearson's
Chi-square test and the deviance test, ...
Simultaneous Model Selection and Estimation for Mean and Association Structures with Clustered Binary Data
association clustered binary data generalized estimating equation logistic regression variable selection
2012/9/17
This paper investigates the property of the penalized estimating equations when both the mean and association structures are modelled. To select variables for the mean and association structures seque...
Learning LiNGAM based on data with more variables than observations
LiNGAM based variables observations
2012/9/17
A very important topic in systems biology is developing statistical methods that automatically find causal relations in gene regulatory net-works with no prior knowledge of causal connectivity. Many m...
Discriminative Sparse Coding on Multi-Manifold for Data Representation and Classification
Discriminative Sparse Coding Multi-Manifold for Data Representation Classification
2012/9/18
Sparse coding has been popularly used as an effective data represen-tation method in various applications, such as computer vision, medical imaging and bioinformatics, etc. However, the conventional s...
Power-law distributions in binned empirical data
power-law distribution heavy-tailed distributions model selec-tion binned data
2012/9/18
Many man-made and natural phenomena, including the intensity of earthquakes, population of cities, and size of international wars, are believed to follow power-law distributions. The accurate identifi...
Bayesian inference on dependence in multivariate longitudinal data
Cholesky decomposition covariance matrix moment-matching oxidative stress random effects shrinkage prior.
2012/9/17
In many applications, it is of interest to assess the dependence structure in multivariate longitudinal data. Discovering such dependence is challenging
due to the dimensionality involved. By concate...
Nested hidden Markov chains for modeling dynamic unobserved heterogeneity in multilevel longitudinal data
composite likelihood EM algorithm latent Markov model pairwise likelihood
2012/9/17
In the context of multilevel longitudinal data, where sample units are collected in clusters, an important aspect that should be accounted for is the unobserved heterogeneity between sample units and ...
Ancestral Inference from Functional Data: Statistical Methods and Numerical Examples
comparative analysis Ornstein-Uhlenbeck process non-parametric Bayesian infer-ence functional phylogenetics ancestral reoncon-struction
2012/9/17
Many biological characteristics of evolutionary inter-est are not scalar variables but continuous functions.Here we use phylogenetic Gaussian process regres-sion to model the evolution of simulated fu...
An Improved Data Assimilation Scheme for High Dimensional Nonlinear Systems
Bayesian Estimation Ensemble Data Assimilation Gaussian Sum Expansion Environmental Control
2012/9/17
Nonlinear/non-Gaussian ltering has broad applications in many areas of life sciences where either the dynamic is nonlinear and/or the probability density function of un-certain state is non-Gaussian....
Agnostic Notes on Regression Adjustments to Experimental Data: Reexamining Freedman's Critique
Analysis of covariance covariate adjustment randomization in-ference sandwich estimator robust standard errors social experiments program evalua-tion
2012/9/17
Freedman [Adv. in Appl. Math.40(2008) 180–193; Ann. Appl.Stat.2(2008) 176–196] critiqued ordinary least squares regression ad-justment of estimated treatment effects in randomized experiments,using Ne...