Sign Up to like & get
recommendations!
0
Published in 2018 at "Econometric Reviews"
DOI: 10.1080/07474938.2014.999499
Abstract: ABSTRACT It is quite common to observe heteroskedasticity in real data, in particular, cross-sectional or micro data. Previous studies concentrate on improving the finite-sample properties of tests under heteroskedasticity of unknown forms in linear models.…
read more here.
Keywords:
nonlinear models;
sample refinement;
heteroskedasticity unknown;
finite sample ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2020 at "Econometric Reviews"
DOI: 10.1080/07474938.2020.1772568
Abstract: Abstract We study the problem of estimating the parameters of a linear median regression without any assumption on the shape of the error distribution – including no condition on the existence of moments – allowing…
read more here.
Keywords:
confidence;
sample generalized;
confidence distributions;
finite sample ... See more keywords
Sign Up to like & get
recommendations!
1
Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3160407
Abstract: Canonical correlation analysis (CCA) has been essential in unsupervised multimodal/multiview latent representation learning and data fusion. Classic CCA extracts shared information from multiple modalities of data using linear transformations. In recent years, deep neural networks-based…
read more here.
Keywords:
cca;
multimodal;
shared information;
analysis ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2017 at "Biometrics"
DOI: 10.1111/biom.12614
Abstract: Alternating logistic regressions is an estimating equations procedure used to model marginal means of correlated binary outcomes while simultaneously specifying a within-cluster association model for log odds ratios of outcome pairs. A recent generalization of…
read more here.
Keywords:
regressions improved;
improved finite;
alternating logistic;
finite sample ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2019 at "Bernoulli"
DOI: 10.3150/18-bej1065
Abstract: The Wasserstein distance between two probability measures on a metric space is a measure of closeness with applications in statistics, probability, and machine learning. In this work, we consider the fundamental question of how quickly…
read more here.
Keywords:
finite sample;
sharp asymptotic;
asymptotic finite;
rates convergence ... See more keywords
Sign Up to like & get
recommendations!
1
Published in 2021 at "Entropy"
DOI: 10.3390/e23050545
Abstract: Finite-sample bounds on the accuracy of Bhattacharya’s plug-in estimator for Fisher information are derived. These bounds are further improved by introducing a clipping step that allows for better control over the score function. This leads…
read more here.
Keywords:
sample bounds;
bounds accuracy;
fisher information;
finite sample ... See more keywords