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The input to the visible units of CRSM is the visual word-count vectors and to learn an optimum fitting distribution for any given set of m data samples ({ mathbb {U}_{1}, mathbb {U}_{2}, ldots, mathbb {U}_{m} }) CRSM attempt to solve the following minimization problem.
The goodness-of-fit results indicated that the best fitting distribution is different for individual homogeneous regions.
This entails a commitment to care for that home and to the fitting distribution of its goods among all.
The accidental snow load on the ground corresponding to a mean return period of 10,000 years is assessed by the best fitting distribution function.
Then, the Akaike information criterion is adopted to screen out the best fitting distribution for each mode from candidate ones.
Here we show only the best fitting distribution among these distributions in Gupta and Ong (2005).
We performed a two-sample Kolmogorov-Smirnov (KS) test to compare the distributions of two data vectors: node indexes (i.e. degrees, hyperdegrees), the samples drawn from the corresponding fitting distribution.
The best fitting distribution is shown in bold.
In the first step, the best fitting distribution was identified.
The best fitting distribution using log-likelihood was the three-parameters generalized extreme value distribution followed by the two-parameter gamma distribution.
The log-normal distribution was chosen after comparing -2log-likelihood statistics for each model and comparing the median observed and predicted survival times to determine the best fitting distribution.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com