Posterior probabilities of membership of repertoires in acoustic clades. by Hal Whitehead, Taylor A Hersh

“…We show how to calculate the Bayesian posterior probabilities that each repertoire is a member of each identity clade, and display this information as a stacked bar graph. …”
Get full text

Incentive-compatible surveys via posterior probabilities by Cvitanić, J, Prelec, D, Radas, S, Šikić, H

“…If the planner also requires a locality condition that ensures that the mechanism payoffs are determined by the respondents’ posterior probabilities of the true state of nature, we prove that, under additional smoothness and sensitivity conditions, the payoff in the truth-telling equilibrium must be a logarithmic function of those posterior probabilities. …”
Get full text

Incentive-compatible surveys via posterior probabilities by Cvitanić, J, Prelec, Drazen, Radas, Sonja, Šikić, H

“…If the planner also requires a locality condition that ensures that the mechanism payoffs are determined by the respondents’ posterior probabilities of the true state of nature, we prove that, under additional smoothness and sensitivity conditions, the payoff in the truth-telling equilibrium must be a logarithmic function of those posterior probabilities. …”
Get full text

Joint Posterior Probability Active Learning for Hyperspectral Image Classification by Shuying Li, Shaowei Wang, Qiang Li

“…However, most current active-learning methods are only concerned with the first two columns of the posterior probability matrix during the sampling phase. When the difference between the first and second-largest posterior probabilities of several samples is proximate, these approaches fail to distinguish them further. …”
Get full text

Adaptive image segmentation algorithm under the constraint of edge posterior probability by Meiling Gong, Jinhui Lan, Changlin Yang, Hongtao Wu, Tao Zhi

“…To solve these problems, the authors proposed an adaptive image segmentation algorithm under the constraint of edge posterior probability. This algorithm first resolves the problem of over‐segmentation by improving the watershed algorithm. …”
Get full text

From <i>p</i>-Values to Posterior Probabilities of Null Hypotheses by Daiver Vélez Ramos, Luis R. Pericchi Guerra, María Eglée Pérez Hernández

“…Minimum Bayes factors are commonly used to transform two-sided <i>p</i>-values to lower bounds on the posterior probability of the null hypothesis, in particular the bound <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>−</mo><mi>e</mi><mo>·</mo><mi>p</mi><mo>·</mo><mo form="prefix">log</mo><mo>(</mo><mi>p</mi><mo>)</mo></mrow></semantics></math></inline-formula>. …”
Get full text

A Software Tool for Estimating Uncertainty of Bayesian Posterior Probability for Disease by Theodora Chatzimichail, Aristides T. Hatjimihail

Subjects: Get full text

TOPSIS missile target selection method supported by the posterior probability of target recognition by Jianqiang Zhang, Jialin Li, Yan Li

Get full text

The influence of misspecified covariance on false discovery control when using posterior probabilities by Ye Liang, Joshua D. Habiger, Xiaoyi Min

“…Specifically, we evaluate the influence on the marginal distribution of local false discovery rate statistics, which are used in many multiple testing procedures and related to Bayesian posterior probabilities. Explicit forms of the marginal distributions under both correctly specified and incorrectly specified models are derived. …”
Get full text

Improved Adaptive Finch Clustering Sonar Segmentation Algorithm Based on Data Distribution and Posterior Probability by Qianqian He, Min Lei, Guocheng Gao, Qi Wang, Jie Li, Jingjing Li, Bo He

Get full text

Object Detection via Active Learning Strategy Based on Saliency of Local Features and Posterior Probability by Meng Wang, Guobao Liu, Haipeng Liu

“…Subsequently, it calculates the posterior entropy based on the posterior probability of the current model&#x2019;s candidate instances. …”
Get full text

Posterior probability and collaborative filtering based Heterogeneous Recommendations model for user/item Application in use case of IoVT by Hai, Tao, Zhou, Jincheng, Lu, Ye

Stability and uncertainty assessment of geoelectrical resistivity model parameters: a new hybrid metaheuristic algorithm and posterior probability density function approach by K. Sarkar, J. V. Tiwari, U. K. Singh

“…Thus, it is superior to examine the histograms and posterior probability density functions (PDFs) of such solutions to exemplify the global solution. …”
Get full text

How useful is the fine-scale mapping of complex trait linkage peaks? Evaluating the impact of additional microsatellite genotyping on the posterior probability of linkage. by Wiltshire, S, Morris, A, McCarthy, M, Cardon, L

“…Increased LOD scores accompany an increased posterior probability of linkage, and large LOD score changes and the presence of dominance at the trait locus accentuate this effect. …”

Remote-Sensing-Based Change Detection Using Change Vector Analysis in Posterior Probability Space: A Context-Sensitive Bayesian Network Approach by Yikun Li, Xiaojun Li, Jiaxin Song, Zihao Wang, Yi He, Shuwen Yang

Subjects: “…change vector analysis in posterior probability space (CVAPS)…”
Get full text

Application of stable isotopes to study movement ecology and diet variation in a migratory songbird by Andrea Contina, Allison K. Pierce, Scott W. Yanco, Eli S. Bridge, Jeffrey F. Kelly, Michael B. Wunder

Subjects: Get full text

Robust Classification Using Posterior Probability Threshold Computation Followed by Voronoi Cell Based Class Assignment Circumventing Pitfalls of Bayesian Analysis of Biomedical Data by Alfred Ultsch, Jörn Lötsch

“…An approach for a robust extension of Bayesian inference is proposed that proceeds in two main steps starting from the Bayesian posterior probabilities. First, cases with low evidence are labeled as “uncertain” class membership. …”
Get full text

Intelligent lung cancer MRI prediction analysis based on cluster prominence and posterior probabilities utilizing intelligent Bayesian methods on extracted gray-level co-occurrence (GLCM) features by Jing Yang, Por Lip Yee, Abdullah Ayub Khan, Hanen Karamti, Elsayed Tag Eldin, Amjad Aldweesh, Atef El Jery, Lal Hussain, Abdulfattah Omar

“…This study is specifically conducted for detailed posterior probabilities analysis to unfold the network associations among the gray-level co-occurrence matrix (GLCM) features. …”
Get full text

On the Probabilty Concept by Bruno De Finetti

Subjects: Get full text

Trajectory-BERT: Trajectory Estimation Based on BERT Trajectory Pre-Training Model and Particle Filter Algorithm by You Wu, Hongyi Yu, Jianping Du, Chenglong Ge

Subjects: Get full text