| 词汇 | posterior-probability |
| 释义 | BETA posterior probabilitycollocation in Englishmeanings of posteriorand probabilityThese words are often used together. Click on the links below to explore the meanings. posterior adjective[ before noun ] uk /pɒsˈtɪə.ri.ər/ us /pɑːˈstɪr.i.ɚ/ anatomy specialized positioned at or towards ... See more at posterior probability noun[ C or U ] uk /ˌprɒb.əˈbɪl.ə.ti/ us /ˌprɑː.bəˈbɪl.ə.t̬i/ the level of possibility of something happening or ... See more at probability Examples of posterior probabilityposterior probability Individuals were assigned to the group with the largest posteriorprobability estimate. A key output of model estimation is the posteriorprobability of group membership. Prior to observing x, this distribution is the prior probability p(h); after observing x, it is the posteriorprobability p(h x). Specifically, the posteriorprobability is proportional to the prior probability and the likelihood function. The highest posteriorprobability corresponds to the most likely linkage phase configuration. The posteriorprobability-updating algorithm can be modified to only update the posteriors after a cer tain amount of inspection data has been received. At the same time, neither effect size, nor confidence interval estimate, nor posteriorprobability can be used to exclude chance as an explanation of data. Posterior mode (maximum posteriorprobability) parameter values can be found by direct numerical optimization of the posteriorprobability. It provides the posteriorprobability for a pair to belong to a class of objects. Accordingly, as required, the posteriorprobability of design is high for the actual world, but low in the alternative worlds. This was corrected by log transforming the dependent variable, that is, the posteriorprobability of membership to the highest physical aggression trajectory. Cortical neurons, in general, could be thought of as feature detectors that compute the posterior probability that their feature has been detected, given their inputs. The posteriorprobability of the aligner sensor rises slightly to 50% because it exists only in one of the remaining hypotheses. One can see why the estimated coefficients becomes stronger once they are weighted by their posteriorprobability. The posteriorprobability of it being the correct model was near 1 .99!, indicating that the model fit the data very well. These examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors. |
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