منابع مشابه
Conditional Dependence in Longitudinal Data Analysis
Mixed models are widely used to analyze longitudinal data. In their conventional formulation as linear mixed models (LMMs) and generalized LMMs (GLMMs), a commonly indispensable assumption in settings involving longitudinal non-Gaussian data is that the longitudinal observations from subjects are conditionally independent, given subject-specific random effects. Although conventional Gaussian...
متن کاملDimensionality and Dependence Problems in Statistical Genomics
Genome studies have become central to a wide range of biological areas. This paper is intended to discuss the state of art and potentiality of using statistics in genome comparison. The problem of dependence and dimensionality in genome data is addressed first. The focus is on using phylogenetic methods in genome comparison, on combining sequence and gene expression data to find transcription s...
متن کاملStatistical Dependence in Markov Random Field Models
Statistical models based on Markov random fields present a flexible means for modeling statistical dependencies in a variety of situations including, but not limited to, spatial problems with observations on a lattice. The simplest of such models, sometimes called “auto-models” are formulated from sets of conditional one-parameter exponential family densities or mass functions. Despite the attr...
متن کاملVoronoi Methods for Assessing Statistical Dependence
In this work, we leverage the intuitive geometry of the Voronoi diagram to develop a new class of methods for quantifying and testing for statistical dependence between real-valued random variables. The contributions of this work are threefold: First, we introduce the utility of probability integral transforms of the datapoints to produce Voronoi diagrams which exhibit desirable properties prov...
متن کاملMeasuring Statistical Dependence with Hilbert-Schmidt Norms
We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate of the Hilbert-Schmidt norm of the cross-covariance operator (we term this a Hilbert-Schmidt Independence Criterion, or HSIC). This approach has several advantages, compared with previous kernel-based independence criteria. Fir...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Modern Physics C
سال: 1996
ISSN: 0129-1831,1793-6586
DOI: 10.1142/s0129183196000326