Non‐parametric Tests for Complete Data

Bagdonavičius, Vilijandas; Kruopis, Julius; Nikulin, Mikhaïl

doi:10.1002/9781118557716

Cited by 42 publications

(14 citation statements)

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“…The test performs a separate analysis for each possible combination of groups available using the W test statistic and associated critical values (Wilcoxon et al, 1970). For larger samples, W is then converted into the Z test statistic (Bagdonavicius et al, 2011). Based on the test statistic or subsequent p value, the H 0 of no difference is either accepted or rejected.…”

Section: Categorical Vs Continuous Variable Analysismentioning

confidence: 99%

An Analysis of Patterns and Trends in United States Stormwater Utility Systems

Kea

Dymond

Campbell

2016

J American Water Resour Assoc

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Several factors, such as municipality location and population, are thought to influence trends among stormwater utilities (SWUs); however, no analysis of the relationship between these factors and SWU characteristics has been performed. This article corroborates hypothesized relationships and identifies trends and patterns in the establishment, funding mechanism, and magnitude of SWUs by analyzing location, population density, home value, and year of establishment for a comprehensive national SWU database with data for 1,490 SWUs. The equivalent residential unit (ERU), a SWU that charges based on impervious area, was the most prevalent funding mechanism in all National Oceanic and Atmospheric Administration Climate Regions of the United States except the West and West‐North‐Central. The ERU was also found in larger cities with high population densities, whereas the Flat Fee, a SWU that charges a single rate for all properties, was found in smaller towns. Higher home values were correlated with higher monthly fees for 28% of the municipalities analyzed. The residential equivalence factor, a SWU that charges based on runoff produced, was popular in municipalities with higher home values, whereas the Flat Fee was popular in municipalities with lower home values. The number of SWUs established increased with Phase I municipal separate stormwater and sewer system (MS4) permit and Phase II small MS4 permit deadlines. Summary tables provide guidance to aid municipalities considering a SWU.

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Section: Categorical Vs Continuous Variable Analysismentioning

confidence: 99%

An Analysis of Patterns and Trends in United States Stormwater Utility Systems

Kea

Dymond

Campbell

2016

J American Water Resour Assoc

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“…Due to the lesser assumptions and the simplicity the methods are widely applicable than parametric methods. The detailed study of the non-parametric methods can be found in [11]- [13].…”

Section: B Non-parametric Density Estimationmentioning

confidence: 99%

Gaussian semi-Markov model based on real video multimedia traffic

Fowler

Sarfraz

Abbas

et al. 2015

2015 IEEE International Conference on Communications (ICC)

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Abstract-The 3rd Generation Partnership Project (3GPP) introduced the new radio access technology, LTE (Long Term Evolution) and LTE-Advanced, which has the capability to provide larger bandwidth and low latencies on a wireless network in order to fulfill the demand of Users' Equipment (UEs) with acceptable Quality of Service (QoS). One of the data-heavy applications that has exploded on the market is Video. This calls for accurate modeling of video traffic. To ensure the quality and correctness of complex systems with Video traffic, it is important to evaluate the behavior of the traffic in the heterogeneous environment. This paper presents measurements on LTE Video traffic which were performed in a real environment. We derived a semi-Markov model which accurately reproduces the statistics of composite Video measurements over LTE network.

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“…The statistics of IGD values are listed in Table II and III. The proposed method is also analyzed statistically with every other algorithms using Mann-Whitney U test [27], which is a nonparametric statistical hypothesis test. The significance results are also presented in Table II and III.…”

Section: B Performance Metricmentioning

confidence: 99%

Multiobjective differential evolution algorithm with opposition-based parameter control

Leung

Zhang

Yuen

2012

2012 IEEE Congress on Evolutionary Computation

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Multiobjective evolutionary algorithms (MOEAs) often have several control parameters, and their performance is highly related to the parameters. A proper set of parameter values is useful for MOEAs in a particular application. This paper addresses the parameter control problem. Inspired by the observations in differential evolution (DE), we proposed a parameter control system using opposition-based learning (OBL). The proposed method contains three conditions which characterize the state of parameters at different evolutionary stages. It keeps good parameters for the current search stage. In case the parameters are bad, it uses OBL to accelerate the finding of good ones. The method is applied to a newly proposed multiobjective DE algorithm (MODEA) which does not control parameters. The resulting algorithm is tested on CEC 2009 test suite comparing with two other recently proposed MOEAs, namely GDE3 and MOEA/D. Experimental results show that the proposed method can significantly improve the performance of MODEA. Moreover, the resulting algorithm significantly outperforms GDE3 and

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Non‐parametric Tests for Complete Data

Cited by 42 publications

References 0 publications

An Analysis of Patterns and Trends in United States Stormwater Utility Systems

An Analysis of Patterns and Trends in United States Stormwater Utility Systems

Gaussian semi-Markov model based on real video multimedia traffic

Multiobjective differential evolution algorithm with opposition-based parameter control

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