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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...
Unified Analysis of Transmit Antenna Selection/Space-Time Block Coding with Receive Selection and Combining over Nakagami-m Fading Channels in the Presence of Feedback Errors
Space-Time Block Coding (STBC) Transmit Antenna Selection (TAS) Receive Antenna Selection (RAS) Maximal-ratio Combining (MRC) Selection Combining (SC) Nakagami-m fading Feedback Errors
2012/9/18
Examining the effect of imperfect transmit antenna selection (TAS) caused by the feedback link errors on the performance of hybrid TAS/space-time block co ding (STBC) with selection combining (SC) (i....
Bayesian Analysis of Multiway Tables in Association Studies: A Model Comparison Approach
Bayesian Analysis Multiway Tables Association Studies Model Comparison Approach
2012/9/17
We consider the problem of statistical inference on unknown quantities structured as a multiway table. We show that such multiway tables are naturally formed by arranging regression coecients in comp...
Integrated analysis of variants and pathways in genome-wide association studies using polygenic models of disease
Integrated analysis of variants pathways genome-wide association studies polygenic models of disease
2012/9/18
Many common diseases are highly polygenic, modulated by a large number genetic factors with small effects on suscep-tibility to disease. These small effects are difficult to map reliably in genetic as...
Asymptotic Generalization Bound of Fisher's Linear Discriminant Analysis
Asymptotic Generalization Bound Fisher's Linear Discriminant Analysis
2012/9/17
Fisher’s linear discriminant analysis (FLDA) is an important dimension reduction method in sta-tistical pattern recognition. It has been shown that FLDA is asymptotically Bayes optimal under the homos...
A variety of resting state neuroimaging data tend to exhibit fractal behavior where their power spectrums follow power-law scaling. Resting state functional connectivity is significantly influenced by...
Fractal analysis of resting state functional connectivity of the brain
Fractal analysis resting state functional the brain
2012/9/17
A variety of resting state neuroimaging data tend to exhibit fractal behavior where their power spectrums follow power-law scaling. Resting state functional connectivity is significantly influenced by...
Sharp analysis of low-rank kernel matrix approximations
Sharp analysis low-rank kernel matrix approximations
2012/9/18
We consider supervised learning problems within the positive-definite kernel framework,such as kernel ridge regression, kernel logistic regression or the support vector machine. With kernels leading t...
A Bayesian Analysis of the Correlations Among Sunspot Cycles
Bayesian Analysis Correlations Among Sunspot Cycles
2012/9/18
Sunspot numbers form a comprehensive, long-duration proxy of so-lar activity and have been used numerous times to empirically investigate the properties of the solar cycle. A number of correlations ha...
Statistical Analysis of Autoregressive Fractionally Integrated Moving Average Models
ARFIMA models long-memory time series Whittle esti-mation exact variance matrix impulse response functions forecasting, R package.
2012/9/17
In practice, several time series exhibit long-range dependence or per-sistence in their observations, leading to the development of a number of estimation and prediction methodologies to account for t...
MMANOVA: A general multilevel framework for multivariate analysis of variance
Bayesian inference Constraints Mixed model Variance components
2012/9/19
Classical analysis of variance requires that model terms be labeled as xed or random and typically culminate by comparing variability from each batch (factor) to variability from errors; without a st...
Sparse linear (or generalized linear) models combine a standard likelihood func-tion with a sparse prior on the unknown coefficients. These priors can conve-
niently be expressed as a maximization ov...
Change point analysis of an exponential model based on Phi-divergence test-statistics: simulated critical points case
Change poin Exponential model Likelihood ratio test
2011/7/19
Recently Batsidis \textit{et al.} (2011) have presented a new procedure based on divergence measures for testing the hypothesis of the existence of a change point in exponential populations.
Functional data analysis of nonlinear modes of variation
Functional data analysis nonlinear modes of variation analysis of variance Fréchet mean Fréchet variance variation in manifolds
2009/9/16
A set of curves or images of similar shape is an increasingly common functional data set collected in the sciences. Principal Component Analysis (PCA) is the most widely used technique to decompose va...
SiZer for time series: A new approach to the analysis of trends
Autocovariance function estimation Local linear fit Scale-space method SiZer Time series
2009/9/16
Smoothing methods and SiZer are a useful statistical tool for discovering statistically significant structure in data. Based on scale space ideas originally developed in the computer vision literature...