Results 41 to 50 of about 165 (146)
Statistical Analysis of Joint Progressive Censoring Data from Gompertz Distribution
, 2022 In this paper, we consider the problems of estimating the unknown parameters as well as predicting the failure times of the removed units in multiple stages of the joint progressively censored sample coming from two Gompertz distributions. The likelihood,
M. Bdair, Omar +2 more
core +1 more source
Structural, Compositional, and Dielectric State Profiling in Label‐Free Single‐Cell Monitoring
Small Methods, EarlyView.Label‐free single‐cell monitoring leverages distinct physical interactions to access structural, compositional, and dielectric states of cells, enabling non‐perturbative, repeatable, and information‐rich measurements across diverse biological contexts. This review organizes representative platforms by intrinsic state variables and connects measurement ...
Changi Baek +6 more
wiley +1 more source
Veterinary Record, EarlyView.Abstract Background Updated targets for measuring transfer of passive immunity (TPI) at the herd level have been suggested, but the current performance of dairy herds in Great Britain is unknown. Methods A cross‐sectional study was performed. Serum total protein (STP) data collected between October 2022 and October 2023 by 21 veterinary practices were ...
George Lindley +3 more
wiley +1 more source
Bayes Estimation of the Logistic Distribution Parameters Based on Progressive Sampling
, 2016 In this paper we develop approximate Bayes estimators of the two parameters logistic distribution. Lindley’s approximation and importance sampling techniques are applied.
Mahmoud, M., Yusuf, M., Rashad, A.
core +1 more source
IEEE Access, 2020 In reliability and life testing experiments, obtaining complete data still consumes lots of time, financial and human supports. A censoring scheme which can have balance between the total testing time, the used number of units and cost in life tests is ...
Mazen Nassar, Saeed A. Dobbah
doaj +1 more source
A tutorial on Bayesian model averaging for exponential random graph models
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The use of exponential random graph models (ERGMs) is becoming prevalent in psychology due to their ability to explain and predict the formation of edges between vertices in a network. Valid inference with ERGMs requires correctly specifying endogenous and exogenous effects as network statistics, guided by theory, to represent the network ...
Ihnwhi Heo +2 more
wiley +1 more source
A Bayes factor framework for unified parameter estimation and hypothesis testing
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The Bayes factor, the data‐based updating factor of the prior to posterior odds of two hypotheses, is a natural measure of statistical evidence for one hypothesis over the other. We show how Bayes factors can also be used for parameter estimation.
Samuel Pawel
wiley +1 more source
, 2019 In this paper, the estimations of linear exponential distribution parameters and the acceleration factor in constant-stress partially-accelerated life tests based on progressive type -II censoring are considered.
A. Fawzy, Mohamad, A. Alasbahi, Ibtesam
core +1 more source
LLM‐based prior elicitation for Bayesian graphical modeling
British Journal of Mathematical and Statistical Psychology, EarlyView.ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski +2 more
wiley +1 more source
Journal of Probability and StatisticsThis work examines Bayesian estimations of the reliability function and the parameters of the Odd Kappa–Exponential distribution using different symmetric and asymmetric loss functions.
Ali A. Al-Shomrani
doaj +1 more source