Results 41 to 50 of about 846,521 (198)

NON-PARAMETRIC MANN-KENDALL AND SEN’S SLOPE ESTIMATE AS A METHOD FOR DETECTING TREND WITHIN HYDRO-METEOROLOGICAL TIME SERIES: A REVIEW

Academy Journal of Science and Engineering, 2023
Climate and water resources are interconnected in a complex way such that a change in any one induces a change in another. Trend analysis is usually employed while assessing the long-term impact of climate variability on the environment, particularly ...
Nura Idris Abdullahi, Shamsudden Mohammed, Yusuf Owoseni, Stephen Ijimdiya, Khalid Suleiman   +4 more
doaj  

Effective Analysis of Interactive Effects with Non-Normal Data Using the Aligned Rank Transform, ARTool and SAS^® University Edition

Horticulturae, 2019
Most statistical techniques commonly used in horticultural research are parametric tests that are valid only for normal data with homogeneous variances.
Edward Durner
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The treatment of ties in non-parametric tests. [PDF]

, 1959
Thesis (M.A.)--Boston UniversityIn most of the non-parametric methods, only a few general assumptions are made concerning the underlying distribution of the population from which a certain sample is drawn. One of the most frequent of these assumptions is
Duenas, Jeannene
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Testing k-monotonicity of a discrete distribution. Application to the estimation of the number of classes in a population

, 2017
We develop here several goodness-of-fit tests for testing the k-monotonicity of a discrete density, based on the empirical distribution of the observations.
Giguelay, Jade, Huet, Sylvie
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Approximate Kernel-Based Conditional Independence Tests for Fast Non-Parametric Causal Discovery

Journal of Causal Inference, 2019
Constraint-based causal discovery (CCD) algorithms require fast and accurate conditional independence (CI) testing. The Kernel Conditional Independence Test (KCIT) is currently one of the most popular CI tests in the non-parametric setting, but many ...
Strobl Eric V., Zhang Kun, Visweswaran Shyam   +2 more
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Maximum Extreme Flow Estimations in Historical Hydrological Series under the Influence of Decadal Variations

Hydrology, 2022
The hypothesis of stationarity is a fundamental condition for the application of the statistical theory of extreme values, especially for climate variables. Decadal-scale fluctuations commonly affect maximum and minimum river discharges.
Marco Antonio Jacomazzi, Antonio Carlos Zuffo, Monzur Alam Imteaz, Vassiliki Terezinha Galvão Boulomytis, Marcus Vinícius Galbetti, Tais Arriero Shinma   +5 more
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Non-Parametric Goodness-of-Fit Tests Using Tsallis Entropy Measures

Entropy
We develop goodness-of-fit (GOF) procedures rooted in Tsallis entropy, with a particular emphasis on multivariate exponential-power (generalized Gaussian) and q-Gaussian models. The GOF statistic compares a closed-form Tsallis entropy under the null with
Mehmet Siddik Cadirci
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Long-Range Dependence in Daily Interest Rate [PDF]

, 2000
We employ a number of parametric and non-parametric techniques to establish the existence of long-range dependence in daily interbank o er rates for four countries.
Ioannidis, C, Monoyios, M
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Assessing the performance of parametric and non‐parametric tests for trend detection in partial duration time series

Journal of Flood Risk Management
The detection of nonstationarities in partial duration time series (PDS) depends on several factors, including the length of the time series, the selected statistical test, and the heaviness of the tail of the distribution.
Renato Amorim, Gabriele Villarini
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Implementation of APSO and Improved APSO on Non-Cascaded and Cascaded Short Term Hydrothermal Scheduling

IEEE Access, 2021
Short-term hydrothermal scheduling (STHTS) is a highly non-linear, multi-model, non-convex, and multi-dimensional optimization problem that has been worked upon for about 5 decades.
Muhammad Salman Fakhar, Syed Abdul Rahman Kashif, Sheroze Liaquat, Akhtar Rasool, Sanjeevikumar Padmanaban, Muhammad Ahmad Iqbal, Muhammad Anas Baig, Baseem Khan   +7 more
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