搜索结果: 1-12 共查到“统计学 interaction”相关记录12条 . 查询时间(0.122 秒)
Backgroud: Epistatic Miniarray Profiles (EMAP) enables the research of genetic interaction as an importan-t method to construct large-scale genetic interaction network. However, high proportion of mis...
Backgroud: Epistatic Miniarray Profiles (EMAP) enables the research of genetic interaction as an importan-t method to construct large-scale genetic interaction network. However, high proportion of mis...
Generalized neighbor-interaction models induced by nonlinear lattices
Nonlinear schrodinger equation the space nonlinear coefficient complex nonlinear lattice
2014/12/24
It is shown that the tight-binding approximation of the nonlinear Schrödinger equation with a periodic linear potential and periodic in space nonlinearity coefficient gives rise to a number of no...
Bayesian semiparametric analysis for two-phase studies of gene-environment interaction
Biased sampling colorectal cancer Dirichlet prior exposure enriched sampling gene-environment independence jointeffects multivariate categorical distribution spike and slab prior
2013/6/14
The two-phase sampling design is a cost-efficient way of collecting expensive covariate information on a judiciously selected subsample. It is natural to apply such a strategy for collecting genetic d...
Reverse Engineering Gene Interaction Networks Using the Phi-Mixing Coefficient
Reverse Engineering Gene Interaction Networks Phi-Mixing Coefficient
2012/9/18
In this paper, we present a new algorithm for reverse-engineering gene interaction networks (GINs) from expression data, by viewing the expres-sion levels of various genes as coupled random variables....
Reverse Engineering Gene Interaction Networks Using the Phi-Mixing Coefficient
Reverse Engineering Gene Interaction Networks Phi-Mixing Coefficient
2012/9/18
In this paper, we present a new algorithm for reverse-engineering gene interaction networks (GINs) from expression data, by viewing the expres-sion levels of various genes as coupled random variables....
Remarks on the statistical study of protein-protein interaction in living cells
Maximum likelihood multi-exponential model model selection FRET FLIM TCSPC
2011/6/20
In this note, we focus on a selection model problem: a monoexponential
model versus a bi-exponential one. This is done in the biological
context of living cells, where small data are available. Clas...
Deep determinism and the assessment of mechanistic interaction between categorical and continuous variables
Methodology (stat.ME) Genomics (q-bio.GN)
2010/12/17
Our aim is to detect mechanistic interaction between the effects of two causal factors on a binary response, as an aid to identifying situations where the effects are mediated by a common mechanism.
Perfect simulation using dominated coupling from the past with application to area-interaction point processes and wavelet thresholding
coupling from the past (CFTP) dominated CFTP exact simulation local stability Markov chain Monte Carlo perfect simulation
2010/3/11
We consider perfect simulation algorithms for locally stable point processes
based on dominated coupling from the past, and apply these methods
in two different contexts. A new version of the algori...
Score Tests for Pairwise Interaction Parameters of Gibbs Point Processes
Score Tests Pairwise Interaction Parameters Gibbs Point Processes
2009/9/17
Score Tests for Pairwise Interaction Parameters of Gibbs Point Processes。
Perfect simulation of spatial point processes using dominated coupling from the past with application to a multiscale area-interaction point process
Perfect simulation spatial point processes dominated coupling multiscale area-interaction point process
2010/3/18
We consider perfect simulation algorithms for locally stable point pro-
cesses based on dominated coupling from the past. A version of the al-
gorithm is developed which is feasible for processes wh...
Statistical testing procedure for the interaction effects of several controllable factors in two-valued input-output systems
Confoundings Contingency tables Controllable factors Covariate matrix Generalized linear models Hierarchical models
2010/4/29
Suppose several two-valued input-output systems are designed by setting the
levels of several controllable factors. For this situation, Taguchi method has proposed
to assign the controllable factors...