Results 11 to 20 of about 392 (92)

Pac-bayesian bounds for sparse regression estimation with exponential weights [PDF]

, 2010
We consider the sparse regression model where the number of parameters $p$ is larger than the sample size $n$. The difficulty when considering high-dimensional problems is to propose estimators achieving a good compromise between statistical and ...
Alquier, Pierre, Lounici, Karim
core   +4 more sources

A unifying approach to the estimation of the conditional Akaike information in generalized linear mixed models

, 2014
The conditional Akaike information criterion, AIC, has been frequently used for model selection in linear mixed models. We develop a general framework for the calculation of the conditional AIC for different exponential family distributions. This unified
Benjamin Saefken, T. Kneib, C. Waveren, S. Greven   +3 more
semanticscholar   +1 more source

On the adaptive elastic-net with a diverging number of parameters [PDF]

, 2009
We consider the problem of model selection and estimation in situations where the number of parameters diverges with the sample size. When the dimension is high, an ideal method should have the oracle property [J. Amer. Statist. Assoc.
Zhang, Hao Helen, Zou, Hui
core   +2 more sources

Ridge regression for the functional concurrent model

, 2018
The aim of this paper is to propose estimators of the unknown functional coefficients in the Functional Concurrent Model (FCM). We extend the Ridge Regression method developed in the classical linear case to the functional data framework.
Tito Manrique, Christophe Crambes, N. Hilgert   +2 more
semanticscholar   +1 more source

Nonconcave penalized estimation in sparse vector autoregression model

Electronic Journal of Statistics, 2020
High dimensional time series receive considerable attention recently, whose temporal and cross-sectional dependency could be captured by the vector autoregression (VAR) model.
Xuening Zhu
semanticscholar   +1 more source

Sparse Conformal Predictors [PDF]

, 2009
Conformal predictors, introduced by Vovk et al. (2005), serve to build prediction intervals by exploiting a notion of conformity of the new data point with previously observed data.
Hebiri, Mohamed
core   +5 more sources

Tensor-Based Algorithms for Image Classification [PDF]

, 2019
Interest in machine learning with tensor networks has been growing rapidly in recent years. We show that tensor-based methods developed for learning the governing equations of dynamical systems from data can, in the same way, be used for supervised ...
Gelß, Patrick, Klus, Stefan
core   +2 more sources

Error bounds for the convex loss Lasso in linear models

, 2017
In this paper we investigate error bounds for convex loss functions for the Lasso in linear models, by first establishing a gap in the theory with respect to the existing error bounds.
Mark H Hannay, P. Deléamont
semanticscholar   +1 more source

Hierarchical Bayes, maximum a posteriori estimators, and minimax concave penalized likelihood estimation

, 2013
Priors constructed from scale mixtures of normal distributions have long played an important role in decision theory and shrinkage estimation. This paper demonstrates equivalence between the maximum aposteriori estimator constructed under one such prior ...
R. Strawderman, M. Wells, E. Schifano
semanticscholar   +1 more source

Bayesian predictive densities for linear regression models under alpha-divergence loss: some results and open problems

, 2010
This paper considers estimation of the predictive density for a normal linear model with unknown variance under alpha-divergence loss for -1
Maruyama, Yuzo, Strawderman, William E.
core   +1 more source