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Posterior Probability Matching and Human Perceptual Decision Making. [PDF]
PLoS Computational Biology, 2015 Probability matching is a classic theory of decision making that was first developed in models of cognition. Posterior probability matching, a variant in which observers match their response probabilities to the posterior probability of each response ...
Richard F Murray +2 more
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Efficient posterior probability mapping using Savage-Dickey ratios. [PDF]
PLoS ONE, 2013 Statistical Parametric Mapping (SPM) is the dominant paradigm for mass-univariate analysis of neuroimaging data. More recently, a bayesian approach termed Posterior Probability Mapping (PPM) has been proposed as an alternative. PPM offers two advantages:
William D Penny, Gerard R Ridgway
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Basic understanding of posterior probability [PDF]
Frontiers in Psychology, 2015 Consider the following task[TaskA]A prenatal test determines whether an unborn child has a chromosomal anomaly. A priori,namely, before undergoing the test, a pregnant woman has a 4% chance of having a child withtheanomaly.Ifawomanhasachildwiththeanomaly,thereisa75%chancethatshehasapositivetest result.
Vittorio eGirotto, Stefania ePighin
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Elastic K-means using posterior probability. [PDF]
PLoS ONE, 2017 The widely used K-means clustering is a hard clustering algorithm. Here we propose a Elastic K-means clustering model (EKM) using posterior probability with soft capability where each data point can belong to multiple clusters fractionally and show the ...
Aihua Zheng +4 more
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Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification. [PDF]
Comput Intell Neurosci, 2015 Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve this
She Q, Ma Y, Meng M, Luo Z.
europepmc +2 more sources
A Software Tool for Estimating Uncertainty of Bayesian Posterior Probability for Disease [PDF]
DiagnosticsThe role of medical diagnosis is essential in patient care and healthcare. Established diagnostic practices typically rely on predetermined clinical criteria and numerical thresholds.
Theodora Chatzimichail +1 more
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Posterior probabilities: Dominance and optimism [PDF]
Economics Letters, 2020 The Bayesian posterior probability of the true state is stochastically dominated by that same posterior under the probability law of the true state. This generalizes to notions of "optimism" about posterior probabilities.
Sergiu Hart, Yosef Rinott
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Posterior Probability on Finite Set [PDF]
Formalized Mathematics, 2012 Summary In [14] we formalized probability and probability distribution on a finite sample space. In this article first we propose a formalization of the class of finite sample spaces whose element’s probability distributions are equivalent with each other.
Hiroyuki Okazaki
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Entropy, 2013 Analysis of knee joint vibration or vibroarthrographic (VAG) signals using signal processing and machine learning algorithms possesses high potential for the noninvasive detection of articular cartilage degeneration, which may reduce unnecessary ...
Fang Zheng +4 more
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The Estimation of Tree Posterior Probabilities Using Conditional Clade Probability Distributions [PDF]
Systematic Biology, 2013 In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas.
B. Larget
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