Results 41 to 50 of about 1,669,943 (280)

Nonparametric Bayes-risk estimation [PDF]

IEEE Transactions on Information Theory, 1971
Two nonparametric methods to estimate the Bayes risk using classified sample sets are described and compared. The first method uses the nearest neighbor error rate as an estimate to bound the Bayes risk. The second method estimates the Bayes decision regions by applying Parzen probability-density function estimates and counts errors made using these ...
Stanley C. Fralick, Richard W. Scott
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BAYES RISKS OF ESTIMATORS OF ESTIMABLE PARAMETERS [PDF]

Bulletin of Mathematical Statistics, 1980
For the estimable parameter of degree 2, throughout this paper, we consider 02 with h2 such that h2(x, x) and h2(x, x)=0 for any x, yEX. As estimators of estimable parameters, U-statistics and differentiable statistical functions are well known. (See, for example, Hoeffding (1948) and von Mises (1947).) For an estimable parameter of degree 1, the U ...
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Universal Bayes Estimators

The Annals of Statistics, 1978
Let $x_1, \cdots, x_n$ be i.i.d. random variables with a distribution depending on the real parameter. Under what conditions is a generalized Bayes estimator independent of the choice of the even loss function? The known answer to this question is that this independence holds if the posterior density is symmetric and unimodal.
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Bayes and empirical bayes estimation of parameter K in negative binomial distribution [PDF]

Journal of Hyperstructures, 2013
In this paper, the problem of estimating the number of successes, k, in a negative binomial distribution for both known and unknown probability p of success are examined by a Bayesian point of view. Also, we introduce two estimations for the parameter of
Masoud Ganji, Nasrin Eghbali, Masoud Azimian   +2 more
doaj   +1 more source

Stimulator of interferon genes agonist augmented antitumor immunity of osimertinib in Egfr‐mutated lung cancer

Molecular Oncology, EarlyView.
Combining osimertinib with the STING agonist ADU‐S100 activates innate and adaptive immunity to overcome the non‐inflamed microenvironment of Egfr‐mutant lung cancer. This combination increases NK and CD8+ T‐cell infiltration, associated with activation of the STING‐IRF3 pathway and local immunogenic cell death.
Jun Nishimura, Tadahiro Kuribayashi, Johannes Brägelmann, Sachi Okawa, Masataka Taoka, Shunta Mori, Tomoka Nishimura, Takaaki Tanaka, Go Makimoto, Kiichiro Ninomiya, Kammei Rai, Eiki Ichihara, Ryohei Katayama, Katsuyuki Hotta, Masahiro Tabata, Yosuke Togashi, Yoshinobu Maeda, Martin L. Sos, Katsuyuki Kiura, Kadoaki Ohashi   +19 more
wiley   +1 more source

Objective Bayes estimation and hypothesis testing : the reference-intrinsic approach [PDF]

, 2005
Conventional frequentist solutions to point estimation and hypothesis testing typically need ad hoc modifications when dealing with non-regular models, and may prove to be misleading.
Juárez, Miguel A.
core  

Empirical Bayes Conditional Density Estimation

Statistica, 2015
The problem of nonparametric estimation of the conditional density of a response, given a vector of explanatory variables, is classical and of prominent importance in many prediction problems since the conditional density provides a more comprehensive ...
Catia Scricciolo
doaj   +1 more source

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

Molecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic, Rafael Stroggilos, Mladen Marinkovic, Ana Djuric, Suzana Stojanovic‐Rundic, Radmila Jankovic, Sergi Castellvi‐Bel, Remond J.A. Fijneman, Antonia Vlahou, Jerome Zoidakis, Milena Cavic   +10 more
wiley   +1 more source

A New Class of Bayes Minimax Estimators of the Mean Matrix of a Matrix Variate Normal Distribution

Mathematics
Bayes minimax estimation is important because it provides a robust approach to statistical estimation that considers the worst-case scenario while incorporating prior knowledge.
Shokofeh Zinodiny, Saralees Nadarajah
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Asymptotic Behavior of Bayes' Estimates

The Annals of Mathematical Statistics, 1964
This paper extends some of the results obtained by Freedman [2]. In Section 1 a class of prior distributions on the space of all substochastic distributions on the positive integers is given, such that along almost all sample sequences the corresponding posterior distributions of the expectations of all bounded functions on the positive integers are ...
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