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In our analysis, the parameters of different distribution models are obtained by applying Maximum Likelihood Estimation (MLE) 47 . To select the best-fit distribution, we compare the models’ Akaike weights 48 derived from Akaike Information Criterion (AIC). Note that analyzing the fitting results, we constantly found that players show a tendency of using simple numbers when allowed to place wagers with arbitrary amounts of virtual currency. As a result, the curves of probability distribution functions appear to peak at simple numbers, and the corresponding cumulative distribution function shows a stepped behavior. This makes the fitting more difficult, especially for the determination of the start of the tail. To address this issue, we choose the start of the tail x min such that we obtain a small Kolmogorov– Smirnov (K– S) distance between the empirical distribution and the fitting distribution, while maintaining a good absolute fit between the complementary cumulative distribution functions (CCDF) of the empirical distribution and the best-fitted distribution. Candidate models for model selection in this paper include exponential distribution, power-law distribution, log-normal distribution, power-law distribution with sharp truncation, power-law distribution with exponential cutoff, and pairwise power-law distribution. More details about parameter fitting and model selection can be found in the article by Clauset et al . article 49 as well as in the previous paper by the authors 8 . Data Availability. The datasets generated and/or analysed during the current study are available from the authors on reasonable request. References, instant roulette बिटकॉइन कैसीनो बिटकॉइन लाइव कैसीनो. 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