We use a recently developed interpretable and unsupervised machine-learning method, the tensorial kernel support vector machine (TK-SVM), to investigate low-temperature classical phase diagram of generalized Heisenberg-Kitaev-$\Gamma$ ($J$-$K$-$\Gamma$) model on honeycomb lattice. Aside from reproducing phases reported by previous quantum studies, our finds hitherto missed nested zigzag-stripy ...

We propose a continuous model for variation in the evolutionary rate across sites and over the phylogenetic tree. We derive exact transition probabilities of substitutions under this model. Changes in rate are modelled using the CIR process, a diffusion widely used in financial applications. The model directly extends the standard gamma distributed rates across site model, with one additional p...

The log-logistic distribution is widely used in different fields of study such as survival analysis, hydrology, insurance, and economics. Recently, Ahsanullah Alzaatreh studied the best linear unbiased estimators for location scale parameters three-parameter model. same authors also propose a shift-invariant Hill estimator unknown shape parameter. In this work, we new estimation method We deriv...

We investigate scattering amplitudes of the reversible $\ensuremath{\theta}$-exact Seiberg-Witten map-based noncommutative (NC) quantum electrodynamics and show explicitly SW map invariance for all types tree-level NCQED two-by-two processes, including M\o{}ller, Bhabha, Compton, pair annihilation, production, light-by-light (LbyL: $\ensuremath{\gamma}\ensuremath{\gamma}\ensuremath{\rightarrow}...

To assess the performance of maximum-likelihood (ML) based Nakagami m parameter estimators, current methods rely on Monte Carlo simulation. In order to enable the analytical performance evaluation of ML-based m parameter estimators, we study the statistical properties of a parameter Δ, which is defined as the log-ratio of the arithmetic mean to the geometric mean for Nakagami-m fading power. Cl...

The most common probabilistic structure of the models used by transportation safety analysts for modeling motor vehicle crashes are the traditional Poisson and Poissongamma (or Negative Binomial) distributions. Since crash data have been shown to exhibit over-dispersion, Poisson-gamma models are usually preferred over Poisson regression models. Up until recently, the dispersion parameter of Poi...

This paper proposes a semi-parametric software reliability model (SRM) based on a mixed gamma distribution, so-called the mixed gamma SRM. In addition, we develop the parameter estimation method for the mixed gamma SRM. Concretely, the estimation method is based on the Bayesian estimation and the parameter estimation algorithm is described by MCMC (Markov chain Monte Carlo) method with grouped ...

Precise spectra of 3C 279 in the 0.5–70 keV range, obtained during two epochs of Swift and NuSTAR observations, are analysed using a near-equipartition model. We apply a one-zone leptonic model with a three-parameter log-parabola electron energy distribution to fit the Swift and NuSTAR X-ray data, as well as simultaneous optical and Fermi-LAT gamma-ray data. The Markov chain Monte Carlo techniq...