[HTML][HTML] Learning under (1+ ϵ)-moment conditions
We study the theoretical underpinning of a robust empirical risk minimization (RERM)
scheme which has been finding numerous successful applications across various data …
scheme which has been finding numerous successful applications across various data …
Bayesian wavelet Stein's unbiased risk estimation of multivariate normal distribution under reflected normal loss: Bayesian wavelet Stein's unbiased risk estimation
In this paper, we consider the generalized Bayes estimator of mean vector parameter for
multivariate normal distribution with unknown mean vector and covariance matrix under …
multivariate normal distribution with unknown mean vector and covariance matrix under …
[PDF][PDF] Critical Quality Source Diagnosis for Dam Concrete Construction Based on Quality Gain-loss Function.
B Wang, Z Li, J Gao, H Vaso - Journal of Engineering Science & …, 2014 - Citeseer
In dam concrete construction process, it not only has quality loss arising from quality
fluctuation, but also gains quality compensation effect due to the mutual cooperation and …
fluctuation, but also gains quality compensation effect due to the mutual cooperation and …
Low and high dimensional wavelet thresholds for matrix-variate normal distribution
H Karamikabir, A Sanati… - … in Statistics-Simulation and …, 2024 - Taylor & Francis
The matrix-variate normal distribution is a probability distribution that is a generalization of
the multivariate normal distribution to matrix-valued random variables. In this paper, we …
the multivariate normal distribution to matrix-valued random variables. In this paper, we …
Estimating the parameter of selected uniform population under the squared log error loss function
KR Meena, M Arshad… - … in Statistics-Theory and …, 2018 - Taylor & Francis
ABSTRACT Let π1,…, π k be k (⩾ 2) independent populations, where π i denotes the
uniform distribution over the interval (0, θ i) and θ i> 0 (i= 1,…, k) is an unknown scale …
uniform distribution over the interval (0, θ i) and θ i> 0 (i= 1,…, k) is an unknown scale …
Estimating parameter of the selected uniform population under the generalized stein loss function
KR Meena, AK Gangopadhyay - Applications and …, 2020 - digitalcommons.pvamu.edu
This paper deals with the problem of estimating scale parameter of the selected uniform
population when sample sizes are unequal. The loss has been measured by the …
population when sample sizes are unequal. The loss has been measured by the …
On admissibility and inadmissibility of estimators after selection under reflected gamma loss function
MN Qomi, N Nematollahi, A Parsian - Hacettepe Journal of …, 2015 - dergipark.org.tr
Let Π1 and Π2 denote two gamma populations with common known shape parameter α> 0
and unknown scale parameters θ1 and θ2, re-spectively. Let X1 and X2 be two independent …
and unknown scale parameters θ1 and θ2, re-spectively. Let X1 and X2 be two independent …
Quality gain-loss function and its empirical analysis in dam concrete construction
B Wang, H Zhou, Z Li, T Fan… - Journal of Coastal …, 2020 - meridian.allenpress.com
ABSTRACT Wang, B.; Zhou, HG; Li, ZY; Fan, TY, and Nie, XT, 2020. Quality gain-loss
function and its empirical analysis in dam concrete construction. In: Guido Aldana, PA and …
function and its empirical analysis in dam concrete construction. In: Guido Aldana, PA and …
[PDF][PDF] Admissible and minimax estimation of the parameters of the selected normal population in two-stage adaptive designs under reflected normal loss function
H Mazarei, N Nematollahi - Probability and Mathematical Statistics, 2019 - academia.edu
In clinical research, one of the key problems is to estimate the effect of the best treatment
among the given k treatments in two-stage adaptive design. Suppose the effects of two …
among the given k treatments in two-stage adaptive design. Suppose the effects of two …
Estimation of the slope parameter in a linear regression model under a bounded loss function
The estimation of the slope parameter of a simple linear regression model in the presence of
nonsample prior information under the reflected normal loss function is considered. Usually …
nonsample prior information under the reflected normal loss function is considered. Usually …