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Evaluation of somatic copy number estimation tools for whole-exome sequencing data
CNV prediction Somatic alterations The Cancer Genome Atlas CNV algorithms
2016/1/26
Evaluation of somatic copy number estimation tools for whole-exome sequencing data.
Evaluation of somatic copy number estimation tools for whole-exome sequencing data
CNV prediction Somatic alterations The Cancer Genome Atlas CNV algorithms
2016/1/20
Evaluation of somatic copy number estimation tools for whole-exome sequencing data.
Strong law of large number of a class of super-diffusions
Spatial autoregression Dynamic panels Fixed e¤ects Quasi-maximum likelihood estima
2016/1/19
Strong law of large number of a class of super-diffusions.
Subspaces that Minimize the Condition Number of a Matrix
Subspaces Minimize Condition Number Matrix
2015/7/9
We define the condition number of a nonsingular matrix on a subspace, and consider the problem of finding a subspace of given dimension that minimizes the condition number of a given matrix. We give a...
PERFECT FORMS OVER TOTALLY REAL NUMBER FIELDS
Quadratic minimum non-zero value integral vector the change of variables
2014/12/24
A rational positive-definite quadratic form is perfect if it can be reconstructed from the knowledge of its minimal nonzero value m and the finite set of integral vectors v such that f(v) = m. This co...
Efficient Estimation of the number of neighbours in Probabilistic K Nearest Neighbour Classification
Bayesian Inference Model Averaging K-free model order estimation
2013/6/14
Probabilistic k-nearest neighbour (PKNN) classification has been introduced to improve the performance of original k-nearest neighbour (KNN) classification algorithm by explicitly modelling uncertaint...
About the posterior distribution in hidden Markov Models with unknown number of states
Hidden Markov models number of components order selection Bayesian statistics posterior distribution
2012/9/19
In this paper, we investigate the asymptotic behaviour of the posterior distribution in hidden Markov models (HMMs) when using Bayesian methodology. We obtain a general asymptotic result, and give con...
Extended BIC for linear regression models with diverging number of relevant features and high or ultra-high feature spaces
Diverging number of parameters Feature selection
2011/7/19
In many conventional scientific investigations with high or ultra-high dimensional feature spaces, the relevant features, though sparse, are large in number compared with classical statistical problem...
Topological Randomness and Number of Edges Predict Modular Structure in Functional Brain Networks
Topological Randomness Number Edges Predict Modular Structure Functional Brain Networks
2011/7/7
In a recent paper, Bassett et al. (2011) have analyzed the static and dynamic organization of functional brain networks in humans.
Perfect Simulation for Mixtures with Known and Unknown Number of components
Bounding chains Dirichlet process Gibbs sampling Mixtures Optimization Perfect Sam-pling
2011/3/24
We propose and develop a novel and effective perfect sampling methodology for simulating from posteriors corresponding to mixtures with either known (fixed) or unknown number of components. For the la...
Perfect Simulation for Mixtures with Known and Unknown Number of components
Bounding chains Dirichlet process Gibbs sampling Mixtures Optimization Perfect Sam-pling
2011/3/23
We propose and develop a novel and effective perfect sampling methodology for simulating from posteriors corresponding to mixtures with either known (fixed) or unknown number of components. For the la...
Multichannel Boxcar Deconvolution with Growing Number of Channels
Adaptivity badly approximable tuples Besov spaces Diophantine approxi-mation functional deconvolution Fourier analysis Meyer wavelets nonparametric estimation wavelet analysis
2011/3/21
We consider the problem of estimating the unknown response function in the multichannel deconvolution model with a boxcar-like kernel which is of particular interest in signal processing. It is known ...
Consistency of Bayesian Linear Model Selection With a Growing Number of Parameters
Bayesian model selection growing number of parameters Posterior model consistency consistency of Bayes factor consistency of posterior odds ratio Gibbs sampling
2011/3/18
Linear models with a growing number of parameters have been widely used in modern statistics. One important problem about this kind of model is the variable selection issue. Bayesian approaches, which...
A brief history of the Fail Safe Number in Applied Research
brief history the Fail Safe Number Applied Research
2010/10/19
Rosenthal's (1979) Fail-Safe-Number (FSN) is probably one of the best known statistics in the context of meta-analysis aimed to estimate the number of unpublished studies in meta-analyses required to...
A sparse regulatory network of copy-number driven expression reveals putative breast cancer oncogenes
sparse regulatory network copy-number driven expression reveals
2010/10/19
The influence of DNA cis-regulatory elements on a gene's expression has been intensively studied. However, little is known about expressions driven by trans-acting DNA hotspots. DNA hotspots harborin...