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For given data, this Demonstration initially shows a histogram and a plot of the sorted data. We can then ask for a plot of the estimated density, two densities, or a two-component mixture density; the mixture density is a weighted sum of two densities. The parameters of the densities are estimated by the maximum likelihood method. The plots of the estimated densities are shown on top of the histogram; this gives an easy visual check of how well the estimated densities fit the histogram. From the estimated densities, we also calculate quantiles, and in the second plot we show the so-called ... - ... plot for quantiles, providing another visual way to check the quality of the fit; the root mean square error (RMSE) of the quantiles summarizes the fit numerically.

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      EUN,LOM,LRE4,work-cmr-id:398117,http://demonstrations.wolfram.com:http://demonstrations.wolfram.com/MaximumLikelihoodEstimationOfOrdinaryAndFiniteMixtureDistrib/,ilox,learning resource exchange,LRE metadata application profile,LRE

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