搜索结果: 1-13 共查到“统计学其他学科 Variables”相关记录13条 . 查询时间(0.078 秒)
The Graphical Identification for Total Effects by using Surrogate Variables
Graphical Identification Total Effects Surrogate Variables
2012/9/19
Consider the case where cause-effect relation-ships between variables can be described as a directed acyclic graph and the corresponding linear structural equation model. This paper provides graphical...
Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables
DAG maximal ancestral graph Markov equivalence
2012/9/18
It is well known that there may be many causal explanations that are consistent with a given set of data. Recent work has been done to represent the common aspects of these explanations into one repre...
Mixing Coefficients Between Discrete and Real Random Variables: Computation and Properties
Mixing Coefficients Between Discrete Real Random Variables Computation Properties
2012/9/17
In this paper we study the problem of estimating the mixing coefficients between two random vari-ables. Three different mixing coefficients are studied,namely alpha-mixing, beta-mixing and phi-mixing ...
Learning LiNGAM based on data with more variables than observations
LiNGAM based variables observations
2012/9/17
A very important topic in systems biology is developing statistical methods that automatically find causal relations in gene regulatory net-works with no prior knowledge of causal connectivity. Many m...
Parameter-Free High-Dimensional Screening Using Multiple Grouping of Variables
Parameter-Free High-Dimensional Screening Multiple Grouping Variables
2012/9/17
Screening is the problem of estimating a superset of the set of non-zero entries in an unknownp-dimensional vector β given nnoisy observations. In the high-dimensional regime, where p > n, screening a...
Estimating a Causal Order among Groups of Variables in Linear Models
Causal Order among Groups Variables in Linear Models
2012/9/19
The machine learning community has recently devoted much attention to the problem of inferring causal relationships from statistical data. Most of this work has focused on uncovering connections among...
New multivariate central limit theorems in linear structural and functional error-in-variables models
explanatory variables domain of attraction of the normal law multivariate Student statistic positive definite matrix
2009/9/16
This paper deals simultaneously with linear structural and functional error-in-variables models (SEIVM and FEIVM), revisiting in this context generalized and modified least squares estimators of the s...
Central limit theorems in linear structural error-in-variables models with explanatory variables in the domain of attraction of the normal law
central limit theorem domain of attraction of the normal law large-sample approximate confidence interval self-normalization Studentization
2009/9/16
Linear structural error-in-variables models with univariate observations are revisited for studying modified least squares estimators of the slope and intercept. New marginal central limit theorems (C...
Selection of variables and dimension reduction in high-dimensional non-parametric regression
dimension reduction high dimension LASSO
2009/9/16
We consider a $l_1$-penalization procedure in the non-parametric Gaussian regression model. In many concrete examples, the dimension $d$ of the input variable $X$ is very large (sometimes depending on...
Penalized model-based clustering with cluster-specific diagonal covariance matrices and grouped variables
EM algorithm High-dimension but low-sample size L1 penalization Microarray gene expression Mixture model Penalized likelihood
2009/9/16
Clustering analysis is one of the most widely used statistical tools in many emerging areas such as microarray data analysis. For microarray and other high-dimensional data, the presence of many noise...
Triangular systems for symmetric binary variables
Graphical Markov models linear in probability models log-linear models recursive generating processes
2009/9/16
We introduce and study distributions of sets of binary variables that are symmetric, that is each has equally probable levels. The joint distribution of these special types of binary variables, if gen...
An exponential inequality for negatively associated random variables
Covariance function Exponential inequality Negative association
2009/9/16
We prove an exponential inequality for negatively associated and strictly stationary random variables. A condition is given for almost sure convergence and the associated rate of convergence is specif...
Functional asymptotic confidence intervals for a common mean of independent random variables
Lindeberg's condition symmetric random variable Student statistic Student process Wiener process functional central limit theorem
2009/9/16
We consider independent random variables (r.v.'s) with a common mean $mu$ that either satisfy Lindeberg's condition, or are symmetric around $mu$. Present forms of existing functional central limit th...