Results 31 to 40 of about 1,044,082 (362)

Flood frequency analysis of Manas River Basin in China under non‐stationary condition

open access: yesJournal of Flood Risk Management, 2021
Incorporating 50 years of flood data for the Manas River Kenswat Hydrological Station from 1957 to 2006, the Pettitt test and Mann–Kendall trend test are used to analyse non‐stationarity of the flood characteristic sequences.
Chaofei He   +4 more
doaj   +1 more source

Characterizing a Joint Probability Distribution by Conditionals

open access: yesJournal of the Royal Statistical Society Series B: Statistical Methodology, 1993
SUMMARY We derive conditions under which a set of conditional and marginal probability distributions will uniquely specify an all-positive joint distribution. Our theoretical result may yield insights into the construction and simulation of multivariate probability models.
Gelman, Andrew, Speed, T. P.
openaire   +2 more sources

Distribution patterns of tau pathology in progressive supranuclear palsy

open access: yesActa Neuropathologica, 2020
Progressive supranuclear palsy (PSP) is a 4R-tauopathy predominated by subcortical pathology in neurons, astrocytes, and oligodendroglia associated with various clinical phenotypes. In the present international study, we addressed the question of whether
G. Kovacs   +22 more
semanticscholar   +1 more source

Global Sensitivity Analysis of Fuzzy Distribution Parameter on Failure Probability and Its Single-Loop Estimation

open access: yesJournal of Applied Mathematics, 2014
An extending Borgonovo’s global sensitivity analysis is proposed to measure the influence of fuzzy distribution parameters on fuzzy failure probability by averaging the shift between the membership functions (MFs) of unconditional and conditional failure
Lei Cheng, Zhenzhou Lu, Luyi Li
doaj   +1 more source

Encounter probability analysis of irrigation water and reference crop evapotranspiration in irrigation district

open access: yesJournal of Hydrology and Hydromechanics, 2018
Based on the data series of the annual reference crop evapotranspiration (ET0) and the amount of irrigation water (IR) from 1970 to 2013 in the Luhun irrigation district, the joint probability distribution of ET0 and IR is established using the Gumbel ...
Zhang Jinping, Li Jiayi, Shi Xixi
doaj   +1 more source

A Simple Markov Chain [PDF]

open access: yesSHS Web of Conferences, 2023
In this paper, Markov chain is used to model the reproduction of the fixed finite population, and use binomial distribution to discuss the probability of gen inheritance between generations population genes and establish transfer matrix ,using ...
Zhai Qian
doaj   +1 more source

New characterization of two-state normal distribution [PDF]

open access: yes, 2014
In this article we give a purely noncommutative criterion for the characterization of two-state normal distribution. We prove that families of two-state normal distribution can be described by relations which is similar to the conditional expectation in ...
Ejsmont, Wiktor
core   +1 more source

Discriminative Joint Probability Maximum Mean Discrepancy (DJP-MMD) for Domain Adaptation [PDF]

open access: yesIEEE International Joint Conference on Neural Network, 2019
Maximum mean discrepancy (MMD) has been widely adopted in domain adaptation to measure the discrepancy between the source and target domain distributions.
Wen Zhang, Dongrui Wu
semanticscholar   +1 more source

Joint probability distribution of winds and waves from wave simulation of 20 years (1989-2008) in Bohai Bay

open access: yesWater Science and Engineering, 2013
The joint probability distribution of wind speed and significant wave height in the Bohai Bay was investigated by comparing the Gumbel logistic model, the Gumbel-Hougaard (GH) copula function, and the Clayton copula function.
Xiao-chen Yang, Qing-he Zhang
doaj   +1 more source

Property prediction for high-chromium high-vanadium steel based on transfer component analysis with few-shot guided

open access: yesJournal of Materials Research and Technology, 2023
The transfer learning model improves accuracy by reducing the marginal and conditional probability distribution discrepancy between source and target domains.
Yuan Liu, Shi-Zhong Wei, Tao Jiang
doaj   +1 more source

Home - About - Disclaimer - Privacy