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Testing Covariates in High Dimensional Regression
Generalized Linear Model High Dimensional Data Hypothe- ses Testing
2016/1/26
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically,we employ the partial covariances be...
Testing the Diagonality of a Large Covariance Matrix in a Regression Setting
Bias-Corrected Test Covariance Diagonality Test High Di- mensional Data
2016/1/26
In multivariate analysis, the covariance matrix associated with a set of vari-ables of interest (namely response variables) commonly contains valuable infor-mation about the dataset. When the dimensio...
Testing Covariates in High Dimensional Regression
Generalized Linear Model High Dimensional Data Hypothe- ses Testing
2016/1/25
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically,we employ the partial covariances be...
Testing Additive Separability of Error Term in Nonparametric Structural Models
Additive Separability Hypotheses Testing Nonparametric Structural Equation Non- separable Models
2016/1/25
This paper considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model non-additively.We...
Testing the statistical significance of an ultra-high-dimensional naïve Bayes classfier
Binary Predictor Hypothesis Testing Na?ve Bayes Supervised Learning
2016/1/25
The na?ve Bayes approach is one of the most popular methods used for classi?cation. Nevertheless, how to test its statistical signi?cance under an ultra-high-dimensional (UHD) setup is not well unders...
Testing the Diagonality of a Large Covariance Matrix in a Regression Setting
Bias-Corrected Test Covariance Diagonality Test High Di- mensional Data Multivariate Analysis
2016/1/20
In multivariate analysis, the covariance matrix associated with a set of vari-ables of interest (namely response variables) commonly contains valuable infor-mation about the dataset. When the dimensio...
Testing Covariates in High Dimensional Regression
Generalized Linear Model High Dimensional Data Hypothe- ses Testing Paid Search Advertising Partial Covariance
2016/1/20
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically,we employ the partial covariances be...
Testing Additive Separability of Error Term in Nonparametric Structural Models
Additive Separability Hypotheses Testing Nonparametric Structural Equation
2016/1/20
This paper considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model non-additively.We...
Testing the statistical significance of an ultra-high-dimensional naïve Bayes classfier
Binary Predictor Hypothesis Testing Na?ve Bayes Supervised Learning
2016/1/20
The na?ve Bayes approach is one of the most popular methods used for classi?cation. Nevertheless, how to test its statistical signi?cance under an ultra-high-dimensional(UHD) setup is not well underst...
Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions
Conditional characteristic function Diffusion processes Empirical likelihood Kernel smoothing L′ evy driven processes
2016/1/19
Markov processes are used in a wide range of disciplines including finance.The transition densities of these processes are often unknown. However, the conditionalcharacteristic functions are more like...
A Residual Based Multiple Testing Procedure for Variance Changepoints
Multiple testing Admissibility Multiple change points Variance change
2016/1/19
In this paper, we approach the variance changepoints detection problem from a multiple testing setting. After proving that the standard Step-Up and Step-Down procedures are inadmissible for the standa...
Supplementary materials for Statistical Estimation and Testing via the Sorted 1 Norm
Supplementary materials Statistical Estimation Sorted 1 Norm
2015/6/17
In this note we give a proof showing that even though the number of false discoveries and the total number of discoveries are not continuous functions of the parameters, the formulas we obtain for the...
Multiple testing of local maxima for detection of peaks in ChIP-Seq data
False discovery rate kernel smoothing matched filter Poisson sequence topological inference
2013/6/14
A topological multiple testing approach to peak detection is proposed for the problem of detecting transcription factor binding sites in ChIP-Seq data. After kernel smoothing of the tag counts over th...
Simple Le Cam optimal inference for the tail weight of multivariate Student $t$ distributions: testing procedures and estimation
local asymptotic normality locally asymptotically maximin tests one-step estimation Student t distribution tail weight
2013/6/14
The multivariate Student $t$ distribution is at the core of classical statistical inference and is also a well-known model for empirical financial data. In the present paper, we propose optimal (in th...
Inference and testing for structural change in time series of counts model
time series of counts Poisson autoregression likelihood estimation change-point semi-parametric test
2013/6/14
We consider here together the inference questions and the change-point problem in Poisson autoregressions (see Tj{\o}stheim, 2012). The conditional mean (or intensity) of the process is involved as a ...