搜索结果: 1-15 共查到“知识库 统计法学”相关记录53条 . 查询时间(1.87 秒)
Quantile correlations and quantile autoregressive modeling
Autocorrelation function Box-Jenkins method Quantile correlation Quantile partial correlation Quantile autoregressive model
2012/11/23
In this paper, we propose two important measures, quantile correlation (QCOR) and quantile partial correlation (QPCOR). We then apply them to quantile autoregressive (QAR) models, and introduce two va...
Clustering and Classification via Cluster-Weighted Factor Analyzers
Cluster-weighted models factor analysis mixturemodels parsimonious models
2012/11/23
In model-based clustering and classification, the cluster-weighted model constitutes a convenient approach when the random vector of interest constitutes a response variable Y and a set p of explanato...
Dependence Structure of Spatial Extremes Using Threshold Approach
Dependence Structure Spatial Extremes Threshold Approach
2012/11/23
The analysis of spatial extremes requires the joint modeling of a spatial process at a large number of stations and max-stable processes have been developed as a class of stochastic processes suitable...
Diagnostics for Respondent-driven Sampling
diagnostics exploratory data analysis hard-to-reachpopulations HIV/AIDS link-tracingsampling non-ignorable design,respondent-driven sampling social networks survey sampling
2012/11/23
Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially groups most at-risk for HIV/AIDS. Data are collected through a peer-referral proc...
Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices
Inserting Vortices Markov Chain Monte-Carlo Asymptotic Performance
2012/11/23
We present a new way of converting a reversible finite Markov chain into a non-reversible one, with a theoretical guarantee that the asymptotic variance of the MCMC estimator based on the non-reversib...
Efficient Estimation of Approximate Factor Models via Regularized Maximum Likelihood
High dimensionality unknown factors principal components sparse matrix conditional sparse thresholding cross-sectional correlation penalized maximum likelihood adaptive lasso heteroskedasticity
2012/11/23
We study the estimation of a high dimensional approximate factor model in the presence of both cross sectional dependence and heteroskedasticity. The classical method of principal components analysis ...
Correlated variables in regression: clustering and sparse estimation
Canonical correlation group Lasso Hierarchical clustering High-dimensional inference Lasso Oracle inequality Variable screening Variable selection
2012/11/23
We consider estimation in a high-dimensional linear model with strongly correlated variables. We propose to cluster the variables first and do subsequent sparse estimation such as the Lasso for cluste...
Monitoring procedure for parameter change in causal time series
Sequential change detection Change-point Causal processes Quasi-maximum likelihood estimator Weak convergence.
2012/11/22
We propose a new sequential procedure to detect change in the parameters of a process $ X= (X_t)_{t\in \Z}$ belonging to a large class of causal models (such as AR($\infty$), ARCH($\infty$), TARCH($\i...
A comparative study of new cross-validated bandwidth selectors for kernel density estimation
kernel density estimation data-adaptive bandwidth selection indirect cross-validation do-validation.
2012/11/22
Recent contributions to kernel smoothing show that the performance of cross-validated bandwidth selectors improve significantly from indirectness. Indirect crossvalidation first estimates the classica...
MMCTest - A Safe Algorithm for Implementing Multiple Monte Carlo Tests
Bootstrap/resampling Computationally Intensive Methods Multiple Comparisons False Discovery Rate Sequential Algorithm
2012/11/22
We are interested in testing multiple hypotheses using tests that can only be evaluated by simulation such as permutation tests or bootstrap tests. This article introduces a sequential algorithm which...
Real-time semiparametric regression
Approximate Bayesian inference Generalized additive models Meaneld vari-ational Bayes Mixed models Online variational Bayes Penalized splines Wavelets
2012/11/22
We develop algorithms for performing semiparametric regression analysis in real time, with data processed as it is collected and made immediately available via modern telecommunications technologies. ...
Negative Binomial Process Count and Mixture Modeling
Negative Binomial Process Count and Mixture Modeling
2012/11/22
The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. We reveal relationships between the Poisson, multinomial, gamma and Dirichlet distrib...
Replicability analysis for Genome-wide Association studies
Replicability analysis Genome-wide Association studies
2012/11/22
The paramount importance of replicating associations is well recognized in the genome-wide associaton (GWA) research community, yet methods for assessing replicability of associations are scarce. Publ...
Likelihood Estimation with Incomplete Array Variate Observations
Likelihood Estimation Incomplete Array Variate Observations
2012/11/22
Missing data estimation is an important challenge with high-dimensional data arranged in the form of an array.In this paper we propose a probability model for partially observed multi-way array data. ...
TIGER: A Tuning-Insensitive Approach for Optimally Estimating Gaussian Graphical Models
TIGER Tuning-Insensitive Approach Optimally Estimating Gaussian Graphical Models
2012/11/22
We propose a new procedure for estimating high dimensional Gaussian graphical models. Our approach is asymptotically tuning-free and non-asymptotically tuning-insensitive: it requires very few efforts...