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As a result, we justify the use of the beta distribution.
The works of [11, 12, 13, 14, 15, 16, 17] and references therein also investigate various representations of binomial sums and zeta functions in a simpler form by the use of the beta function and by means of certain summation theorems for hypergeometric series.
In the next corollary, we also make use of the beta function of Euler type, which is for x, y > 0 defined as β ( x, y ) = ∫ 0 1 t x − 1 ( 1 − t ) y − 1 d t = Γ ( x ) Γ ( y ) Γ ( x + y ).
Use of the beta regression model has been increasing in recent years.
This is a consequence of the use of the beta distribution in the ELISA model.
Johnson et al. [ 1] cite numerous instances where the beta distribution has been used in theory/practice and champion increased use of the beta distribution in applied research settings.
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Several trials are under way around the world, investigating the use of the beta-blocker propranolol (more commonly used to treat high blood pressure) in breast, ovarian and other cancers.
The crack growth propagation rate is one order of magnitude smaller with the use of the beta-nucleating agent compared to the alpha polymer.
We show that the use of the beta-binomial model makes it possible to determine accurate credible intervals even in data which exhibit substantial overdispersion.
The use of the beta-PERT distribution was also able to lessen the uncertainty caused by insufficient information or biased opinions.
The use of the beta-divergence distortion at the NMF framework makes it necessary to fit the parameter β up to the value which obtains the best results as possible.
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