Statistical analysis of extreme events such as flood is often carried out to predict large return period events. The behaviour not only involves heavy-tailed distributions but also skewed distributions, similar the four-parameter Kappa distribution (K4D). In general, this covers many generalized logistic (GLD), value (GEV), Pareto (GPD), and so on. To utilize these we have estimate parameters a...

Abstract In this paper, we have obtained the exact expression and recurrence relations for single moments of order statistics arising from Sushila distribution. We also L-moments, TL-moments distribution used them to find L-moment TL-moment estimators parameters The are using method maximum likelihood. Further, by these likelihood (MLEs), MLEs measures reliability considered Monte Carlo simulat...

Estimation of any probability distribution parameters is vital because imprecise and biased estimates can be misleading. In this study, we investigate a flexible power function distribution and introduced new two methods such as, probability weighted moments, and generalized probability weighted methods for its parameters. We compare their results with L-moments, trimmed L-moments by a simulati...

This paper proposed a method that combines Polar Fourier Transform, color moments, and vein features to retrieve leaf images based on a leaf image. The method is very useful to help people in recognizing foliage plants. Foliage plants are plants that have various colors and unique patterns in the leaf. Therefore, the colors and its patterns are information that should be counted on in the proce...

Owing to their extensive application in the field of robust estimation, the derivation of the distributions of linear combinations of order statistics or L-statistics and the computation of their moments has been approached in several ways. In this paper we use the properties of divided differences to obtain expressions for moments of some order statistics which arise as special cases of L-stat...

Abstract. We give a new heuristic for all of the main terms in the integral moments of various families of L-functions. The results agree with previous conjectures for the leading order terms. Our conjectures also have an almost identical form to exact expressions for the corresponding moments of the characteristic polynomials of either unitary, orthogonal, or symplectic matrices, where the mom...

Identifying the nature of magnetism, itinerant or localized, remains a major challenge in condensed-matter science. Purely localized moments appear only in magnetic insulators, whereas itinerant moments more or less co-exist with localized moments in metallic compounds such as the doped-cuprate or the iron-based superconductors, hampering a thorough understanding of the role of magnetism in phe...

, where C0 = ∫ 1 0 f(t)dt. j ∼ scale, k ∼ position. Key properties: 1. vanishing moments: We say ψ has M vanishing moments when ∫ 1 0 tψj,k(t)dt = 0 form = 0, 1, . . . ,M− 1 This means the wavelet is “blind” to polynomial segment with degree α ≤M − 1 2. compact support: a daubechies wavelet with M vanishing moments has support ∝ 2M. Together, these properties imply that only O(l log n) nonzero ...

The first part of this article deals with fitting of regression equations for the sampling properties, variance of L-standard deviation (l2), and bias and variance of L-skewness (t3), based on Monte-Carlo simulation results, for generalised Normal (Lognormal-3) and Pearson-3 distributions. These fitted equations will be useful in formulating goodness-of-fit test statistics in regional frequency...