Probability Models with Discrete and Continuous Parts
نویسندگان
چکیده
In mathematical statistics courses, students learn that the quadratic function is minimized when x mean of random variable X, and graphs this for any two distributions X are simply translates each other. We focus on problem minimizing defined by in context mixtures probability discrete, absolutely continuous, singular continuous types. This important, example, Bayesian statistics, one attempts to compute decision function, which minimizes expected risk with respect an absolute error loss function. Although literature considers problem, it does so only under restrictive conditions distribution by, assuming corresponding cumulative discrete or continuous. By using Riemann-Stieltjes integration, we prove a theorem, solves minimization completely general X. also illustrate our result presenting examples involving types, Cantor distribution, case Finally, theorem evaluates y(x) has distribution.
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ژورنال
عنوان ژورنال: Open Journal of Statistics
سال: 2022
ISSN: ['2161-7198', '2161-718X']
DOI: https://doi.org/10.4236/ojs.2022.121006