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DATA-DRIVEN SCORE TESTS FOR HOMOSCEDASTIC LINEAR REGRESSION MODEL:ASYMPTOTIC RESULTS
Efficient score hypothesis testing data-driven test linear regression selection rule
2009/9/18
We describe and investigate new tests for testing the
validity of a semiparametric random-design linear regression model.
The tests were introduced in Inglot and Ledwina (2006a, b). We repeat
here ...
Diagnostic Methods in Elliptical Linear Regression Models
Diagnostic Methods Elliptical Linear Regression Models
2009/9/18
Diagnostic Methods in Elliptical Linear Regression Models。
Corrected Likelihood Ratio Tests in Class of Symmetric Linear Regression Models
Likelihood Ratio Tests Symmetric Linear Regression Models
2009/9/18
Corrected Likelihood Ratio Tests in Class of Symmetric Linear Regression Models。
Theoretical properties of Cook's PFC dimension reduction algorithm for linear regression
Principal Components Principal Fitted Components random matrix theory regression
2009/9/16
We analyse the properties of the Principal Fitted Components (PFC) algorithm proposed by Cook. We derive theoretical properties of the resulting estimators, including sufficient conditions under which...
Exact Distributions of R2 and Adjusted R2 in a Linear Regression Model with Multivariate t Error Terms
adjusted R2 exact distribution interval estimation multivariate t error terms R2
2009/3/9
In this paper we consider a linear regression model when error terms obey a multivariate t distribution, and examine the effects of departure from normality of error terms on the exact distributions o...
PENALIZED TRIMMED SQUARES AND A MODIFICATION OF SUPPORT VECTORS FOR UNMASKING OUTLIERS IN LINEAR REGRESSION
robust regression mixed integer programming penalty method least trimmed squares identifying outliers support vector machines
2009/2/25
We consider the problem of identifying multiple outliers in linear regression models.
We propose a penalized trimmed squares (PTS) estimator, where penalty costs for discarding outliers are inserted ...
Smoothing splines estimators for functional linear regression
Functional linear regression functional parameter functionalvariable smoothing splines
2010/3/18
The paper considers functional linear regression, where scalar responses
Y1, . . . ,Yn are modeled in dependence of random functions
X1, . . . ,Xn. We propose a smoothing splines estimator for the f...
Risk bounds in linear regression through PAC-Bayesian truncation
Linear regression Generalization error Shrinkage PAC-Bayesian theorems Risk bounds Robust statistics Resistant estimators
2010/3/18
We consider the problem of predicting as well as the best linear combination
of d given functions in least squares regression, and variants of this problem including
constraints on the parameters of...
The sparsity and bias of the Lasso selection in high-dimensional linear regression
Penalized regression high-dimensional data variable selection bias rate consistency spectral analysis random matrices
2010/4/30
Meinshausen and Buhlmann [Ann. Statist. 34 (2006) 1436–1462]
showed that, for neighborhood selection in Gaussian graphical models,
under a neighborhood stability condition, the LASSO is consistent,
...
Prediction in functional linear regression
Bootstrap covariance dimension reduction eigenfunction eigenvalue eigenvector functional data analysis
2010/4/26
There has been substantial recent work on methods for estimating
the slope function in linear regression for functional data analysis.
However, as in the case of more conventional finite-dimensional...