Results 31 to 40 of about 44,901 (263)

Improving for Network Traffic Bayes Classification Method Based on Correlation Information [PDF]

Jisuanji gongcheng, 2016
With the rapid growth of network applications,the efficiency of traditional network traffic classification method based on ports and payloads is reduced greatly.Meanwhile,most traffic flow classification methods do not consider the correlation among the ...
ZHAO Ying,TAN Yang
doaj   +1 more source

Parameter Estimation of Lindley Distribution Based on Progressive Type-II Censored Competing Risks Data with Binomial Removals

Mathematics, 2019
The competing risk model based on Lindley distribution is discussed under the progressive type-II censored sample data with binomial removals. The maximum likelihood estimation of the unknown parameters of the distribution is established.
Jiaxin Nie, Wenhao Gui
doaj   +1 more source

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.
openaire   +3 more sources

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 ...
openaire   +2 more sources

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

Association Between Dinutuximab Beta Exposure and Post‐End‐of‐Treatment Survival in Neuroblastoma: A Weighted Patient‐Level Analysis of Three Clinical Studies

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Objectives The association between exposure to dinutuximab beta (DB) and event‐free survival (EFS) or overall survival (OS) of neuroblastoma patients was assessed using data collected during three clinical trials (five cohorts). Methods A systematic review (March 2026) was conducted to identify relevant studies (prospective; registered DB ...
Przemysław Holko, Holger N. Lode, Alberto Garaventa, Carla Manzitti, Roberto Luksch, Dominique Valteau‐Couanet, Marion Gambart, John Anderson, Juliet Gray, Adela Canete, Lucas Moreno, Aleksandra Wieczorek, Cormac Owens, Shifra Ash, Isaac Yaniv, Genevieve Laureys, Hans Loibner, Katarzyna Śladowska, Ruth Ladenstein, Paweł Kawalec   +19 more
wiley   +1 more source

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

Establishment of a humanized patient‐derived xenograft mouse model of high‐grade serous ovarian cancer for preclinical evaluation of combination immunotherapy

Molecular Oncology, EarlyView.
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric, Line Bjørge, Martine Rott Lode, Cecilie Fredvik Torkildsen, Pia Aehnlich, Rammah Elnour, Daniela Elena Costea, Lars Andreas Akslen, Liv Cecilie Vestrheim Thomsen, Emmet McCormack, Katrin Kleinmanns   +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
doaj   +1 more source

Bayes Estimation with Convex Loss

The Annals of Mathematical Statistics, 1963
Let $X$ be a generalized random variable taking values in an abstract set $\mathscr{X}$ on which is defined an appropriate $\sigma$-field of subsets. Suppose that the distribution of $X$ depends on a real parameter $\Theta$ and that it is desired to estimate the value of $\Theta$ from an observation on $X$.
DeGroot, M. H., Rao, M. M.
openaire   +2 more sources