Coalescence (statistics)
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In statistics, coalescence refers to the merging of independent probability density functions. It contrasts with the simpler, erroneous approach called conflation.
Conflation
[edit]Conflation refers to the merging of independent probability density functions using simple multiplication of the constituent densities.[1] The Multiplication Rule disregards that the probability of occurrence in each frequency class changes proportionally to the probability reference base accumulated in the considered class.
Coalescence
[edit]Unfortunately, conflation generates a joint density that suffers from a mean-biased expected value and an overly optimistic standard deviation. The conditional nature of the issue imposes an elementary Kolmogorovian-Bayesian reassessment.[2] This shortcoming is satisfactorily solved by the coalescense method.
Coalesced density function
[edit]The coalesced density function d(x) of n independent probability density functions d1(x), d2(x), …, dk(x), is equal to the reciprocal of the sum of the reciprocal densities:
References
[edit]- ^ Hill Th. P., Miller J., Fox R. F., ‘How to Combine Independent Data Sets for the Same Quantity’, Chaos (Woodbury, 2011) 1-20.
- ^ Van Droogenbroeck, Frans J., 'Coalescence, unlocking insights in the intricacies of merging independent probability density functions' (2025).