Results 241 to 250 of about 6,276,816 (299)

A Multicenter, Open‐Label, Phase 2 Trial Comparing Crizanlizumab Combined With Standard Therapy to Standard Therapy Alone on Renal Function in Patients With Sickle Cell Nephropathy (STEADFAST)

American Journal of Hematology, EarlyView.
Kenneth I. Ataga, Pablo Bartolucci, Santosh L. Saraf, Vimal K. Derebail, Adlette Inati, Jeffrey D. Lebensburger, Laurie DeBonnett, Rodolfo D. Cancado, Claire C. Sharpe   +8 more
wiley   +1 more source

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A Quasi-Bayes Estimate of the Failure Intensity of a Reliability-Growth Model

IEEE Transactions on Reliability, 1981
J. J. Higgins, C. Tsokos
exaly   +2 more sources

Bayes estimate of the noncentrality parameter in multivariate analysis

Communications in Statistics - Theory and Methods, 1974
D. Waal
exaly   +2 more sources

The umvue and bayes estimate of reliability of mixed failure time distribution

Communications in Statistics Part B: Simulation and Computation, 2000
K Muralidharan
exaly   +2 more sources

Bayes Estimate and Inference for Entropy and Information Index of Fit

Econometric Reviews, 2008
Thomas Mazzuchi, Refik Soyer, Ehsan Soofi   +2 more
exaly   +2 more sources

Variance of Bayes estimates

IEEE Transactions on Information Theory, 1971
This paper contains an analysis of the performance of Bayes conditional-mean parameter estimators. The main result is that on a finite parameter space such estimates exhibit a mean-square error that diminishes exponentially with the number of observations, the observations being assumed to be independent.
openaire   +1 more source

Bayes empirical Bayes estimation of a poisson mean

Statistics & Probability Letters, 1985
In the empirical Bayes (EB) decision problem consisting of squared error estimation of a Poisson mean, a prior distribution \(\Lambda\) is placed on the gamma family of prior distributions to produce Bayes EB estimators which are admissible. A subclass of such estimators is shown to be asymptotically optimal (a.o.).
openaire   +2 more sources

A widely applicable Bayesian information criterion

Journal of machine learning research, 2012
A statistical model or a learning machine is called regular if the map taking a parameter to a probability distribution is one-to-one and if its Fisher information matrix is always positive definite. If otherwise, it is called singular.
Sumio Watanabe
semanticscholar   +1 more source

Some Comments on “Bayes” Estimators

The American Statistician, 1973
(1973). Some Comments on “Bayes” Estimators. The American Statistician: Vol. 27, No. 1, pp. 12-14.
G. C. Tiao, G. E. P. Box
openaire   +1 more source