A two-stage procedure is proposed for the generation of random variates from a multinomial distribution. In the first stage we propose that cell frequencies be generated as random deviates from a ...

Somer G. Anderson is CPA, doctor of accounting, and an accounting and finance professor who has been working in the accounting and finance industries for more than 20 years. Her expertise covers a ...

Here we propose a method to extremely accelerate NAS, without reinforcement learning or gradient, just by sampling architectures from a distribution and comparing these architectures, estimating their ...

Here, we provide a self-explained R code (SDM-Simulations.R) for repoduce all the results presented in our manuscript. randomized_single_species_distribution.rds - the results of numeric simulation – ...

A test based on the maximum adjusted residual from multinomial models, namely, the M test, is proposed. Sharp bounds on its critical values are provided for the multinomial case, while for the two-way ...

Instead of maximum-likelihood or MAP, Bayesian inference encourages the use of predictive densities and evidence scores. This is illustrated in the context of the multinomial distribution, where ...

Abstract: The probability of a particular outcome of a multinomial trial may depend on the trial number. The generalized multinomial distribution describes such an experiment. A mathematical statement ...

Abstract: Architectures obtained by Neural Architecture Search (NAS) have achieved highly competitive performance in various computer vision tasks. However, the prohibitive computation demand of ...

This contribution deals with a generative approach for the analysis of textual data. Instead of creating heuristic rules forthe representation of documents and word counts, we employ a distribution ...