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QPDs: Converting Quantiles to Continuous Distributions

Quantile-Parameterized Distributions (QPDs) were initially developed for decision analysts to easily transform expert-estimated quantiles into continuous probability distributions. These distributions have also found application in fitting simulation output data, allowing for the representation of Cumulative Distribution Functions (CDFs) and Probability Density Functions (PDFs) as continuous, closed-form distributions. AI

RANK_REASON The item describes a statistical method and its applications, fitting the research category. [lever_c_demoted from research: ic=1 ai=0.4]

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QPDs: Converting Quantiles to Continuous Distributions

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COVERAGE [1]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    `The original applications of QPDs were by decision analysts wishing to conveniently convert expert-assessed quantiles (e.g., 10th, 50th, and 90th quantiles) in

    `The original applications of QPDs were by decision analysts wishing to conveniently convert expert-assessed quantiles (e.g., 10th, 50th, and 90th quantiles) into smooth continuous probability distributions. QPDs have also been used to fit output data from simulations in order to…