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Poisson-PDNN: Modeling non-uniform read distribution in RNA-seq data
Poisson-PDNN Modeling non-uniform distribution in RNA-seq data
2016/1/25
RNA-Seq is a powerful new technology to comprehensively analyze the transcriptome of any given cells. An important task in RNA-Seq data analysis is quantifying the expression levels of all transcripts...
Poisson-PDNN: Modeling non-uniform read distribution in RNA-seq data
Poisson-PDNN Modeling non-uniform distribution RNA-seq data
2016/1/20
RNA-Seq is a powerful new technology to comprehensively analyze the transcriptome of any given cells. An important task in RNA-Seq data analysis is quantifying the expression levels of all transcripts...
The Lasso under Poisson-like Heteroscedasticity
Lasso Poisson-like Model Sign Consistency Heteroscedas- ticity
2016/1/19
The performance of the Lasso is well understood under the assumptions of the standard sparse linear model with homoscedastic noise. However, in several applications, the standard model does not descri...
A Liapunov Bound for Solutions of Poisson’s Equation
Markov chain Markov process Poisson equation Liapounov function
2015/7/8
In this paper we consider ψ-irreducible Markov processes evolving in discrete or continuous time on a general state space. We develop a Liapounov function criterion that permits one to obtain explicit...
复旦大学公共卫生学院卫生统计学课件 Poisson分布资料的统计检验。
复旦大学公共卫生学院卫生统计学课件 poisson分布。
Species dynamics in the two-parameter Poisson-Dirichlet diffusion model
alpha diversity infinite-alleles model infinite dimensional dimensional diffusion mutation rate Poisson-Dirichlet distribution weak convergence
2013/6/14
The recently introduced two-parameter infinitely-many neutral alleles model extends the celebrated one-parameter version, related to Kingman's distribution, to diffusive two-parameter Poisson-Dirichle...
Smoothing effect of Compound Poisson approximation to distribution of weighted sums
characteristic function concentration function compound Poisson distribution Kolmogorov norm weighted random variables.
2013/4/27
The accuracy of compound Poisson approximation to the sum $S=w_1S_1+w_2S_2+...+w_NS_N$ is estimated.
Here $S_i$ are sums of independent or weakly dependent random variables, and $w_i$ denote weights...
Generalized Interference Models in Doubly Stochastic Poisson Random Fields for Wideband Communications: the PNSC(alpha) model
Interference models Cox Process Doubly Stochastic Poisson Stable Process Isotropicα-stable Complexα-stable
2012/9/19
A general stochastic model is developed for the total interference in wideband systems, denoted as the PNSC(α) Interference Model. It allows one to obtain, analytic representations in situations where...
Optimal inferential models for a Poisson mean
Belief function constraint plausibility function predic-tive random set recursive ordering score function validity.
2012/9/18
Statistical inference on the mean of a Poisson distribution is a fundamentally important problem with modern applications in, e.g., particle physics. The dis-creteness of the Poisson distribution make...
We consider a basic problem in unsupervised learning: learning an unknown \emph{Poisson Binomial Distribution} over $\{0,1,...,n\}$. A Poisson Binomial Distribution (PBD) is a sum $X = X_1 + ... + X_n...
Intensity estimation of non-homogeneous Poisson processes from shifted trajectories
Poisson processes Random shifts Intensity estimation Deconvolution Meyer wavelets Adaptive estimation Besov space Minimax rate
2011/6/20
This paper considers the problem of adaptive estimation of a non-homogeneous intensity
function from the observation of n independent Poisson processes having a common intensity
that is randomly shi...
Semiparametric Bivariate Zero-Inflated Poisson Models with Application to Studies of Abundance for Multiple Species
Benthic fish Bivariate Poisson Hierarchical Bayes Missouri River Pspline Zero-inflated Poisson
2011/6/17
Ecological studies involving counts of abundance, presence-absence or occupancy rates
often produce data having a substantial proportion of zeros. Furthermore, these types of
processes are typically...
A Poisson Mixed Model with Nonnormal Random Effect Distribution
Count data Generalized log-gamma distribution Multivariate negative binomial distribution Overdispersion Random-effect models
2011/6/17
We propose in this paper a random intercept Poisson model in which the random effect distribution
is assumed to follow a generalized log-gamma (GLG) distribution. We derive the first two moments
for...
Heavy traffic limit theorems for a queue with Poisson ON/OFF long-range dependent sources and general service time distribution
reflecting fractional Brownian motion reflecting Gaussian process longrange dependence queueing process weak convergence
2011/6/21
In Internet environment, traffic flow to a link is typically modeled by superposition of
ON/OFF based sources. During each ON-period for a particular source, packets arrive
according to a Poisson pr...