Results 81 to 90 of about 212,322 (298)

The Empirical Bayes Estimators of the Variance Parameter of the Normal Distribution with a Normal-Inverse-Gamma Prior Under Stein’s Loss Function

Axioms
For the hierarchical normal and normal-inverse-gamma model, we derive the Bayesian estimator of the variance parameter in the normal distribution under Stein’s loss function—a penalty function that treats gross overestimation and underestimation equally ...
Ying-Ying Zhang
doaj   +1 more source

"Minimax Empirical Bayes Ridge-Principal Component Regression Estimators" [PDF]

In this paper, we consider the problem of estimating the regression parameters in a multiple linear regression model with design matrix A when the multicollinearity is present.
Tatsuya Kubokawa, M. S. Srivastava
core  

On minimaxity and admissibility of hierarchical Bayes estimators [PDF]

, 2006
This paper obtains conditions for minimaxity of hierarchical Bayes estimators in the estimation of a mean vector of a multivariate normal distribution. Hierarchical prior distributions with three types of second stage priors are treated.
Kubokawa, Tatsuya, Tatsuya Kubokawa, William E. Strawderman, Strawderman, William E.   +3 more
core   +1 more source

The Association of Physical Function With Psychosocial Patient‐Reported Outcomes in People With Systemic Lupus Erythematosus

Arthritis Care &Research, EarlyView.
Objective To evaluate how modifiable psychosocial factors and fatigue relate to physical functioning in patients with systemic lupus erythematosus (SLE). Methods In this cross‐sectional study of two demographically distinct cohorts (Approaches to Positive, Patient‐Centered Experiences of Aging with Lupus [APPEAL] and California Lupus Epidemiology Study
Mrinalini Dey, Jessica Fitzpatrick, Maria Dall'Era, Charmayne Dunlop‐Thomas, Courtney Hoge, S. Sam Lim, Patricia P. Katz, Jinoos Yazdany, Laura C. Plantinga   +8 more
wiley   +1 more source

The 3-component mixture of power distributions under Bayesian paradigm with application of life span of fatigue fracture

Scientific Reports
Mixture distributions are naturally extra attractive to model the heterogeneous environment of processes in reliability analysis than simple probability models.
Tahir Abbas, Muhammad Tahir, Muhammad Abid, Samavia Munir, Sajid Ali   +4 more
doaj   +1 more source

An analytical investigation of estimators for expected asset returns from the perspective of optimal asset allocation [PDF]

In the present work I derive the risk functions of 5 standard estimators for expected asset returns which are frequently advocated in the literature, viz the sample mean vector, the James-Stein and Bayes-Stein estimator, the minimum-variance estimator ...
Frahm, Gabriel
core  

Empirical Bayes minimax estimators of matrix normal means [PDF]

, 1991
The paper considers estimation of matrix normal means. A class of empirical Bayes estimators is proposed which dominates the maximum likelihood estimator simultaneously for many quadratic losses.
Shieh, Gwowen, Ghosh, Malay
core   +1 more source

Photo‐Switchable Molecular Module Programming PET Biodegradation in Aquatic Environments

Advanced Functional Materials, EarlyView.
We address the plastic durability paradox by integrating an itaconic acid–derived pyrrolidone module into polymer backbones. Sunlight in water triggers Norrish Type I ring‐opening and hydrophilization, enabling rapid biodegradation into nontoxic minerals.
Mohammad Asif Ali, Jixin Zheng, Satoshi Wakai, Jie Liu, Hidetaka Nomaki, Misato Tsukatani, Noriyuki Isobe, Jingcheng Sang, Yuriko Aoki, Hideo Okamura, Daisuke Sasaki, Chiaki Ogino, Yuzo Yamazaki, Takashi Nishikaze, Kenji Takada, Maiko K. Okajima, Tatsuo Kaneko   +16 more
wiley   +1 more source

Deleted Estimates of the Bayes Risk

The Annals of Statistics, 1973
Consider the usual decision theoretic situation where one observes a random vector $X$ from which an estimate of its classification $\theta \in \{0, 1\}$ is to be made. If one knows the a priori probabilities for $\theta$ and the conditional densities of $X$ given $\theta$ then the smallest probability of error which can be achieved is called the Bayes
openaire   +3 more sources

Bayes linear covariance matrix adjustment [PDF]

, 1995
In this thesis, a Bayes linear methodology for the adjustment of covariance matrices is presented and discussed. A geometric framework for quantifying uncertainties about covariance matrices is set up, and an inner-product for spaces of random matrices ...
Wilkinson, Darren James
core