A Multivariate Extension of the Correlation Ratio

Shaffer, Juliet Popper; Gillo, Martin W.

doi:10.1177/001316447403400305

Cited by 22 publications

(2 citation statements)

References 4 publications

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“…The present research concerns the multivariate correlation measure and review its historical background. After Hotelling (1936) and Cramer and Nicewander (1979), several authors concerned on the measure of vector correlation, namely: Kshirsagar (1969), Coxhead (1974), Shaffer and Gillo (1974) and Cramer and Nicewander (1979). In most of these studies, the proposed correlation measures are a function of canonical correlation.…”

Section: Network Construction Of Sectorsmentioning

confidence: 99%

Network Topology of Renewable Energy Companies: Minimal Spanning Tree and Sub-Dominant Ultrametric for the American Stock

Kazemilari

Mohamadi

Mardani

et al. 2019

Technological and Economic Development of Economy

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Renewable energy has become a significant market player after the turn of the millennium. Wind, solar, smart grid and further renewable energy stocks have experienced both serious up and down trends since that time. In this paper, computed the Minimal Spanning Tree (MST) and Sub-Dominant Ultrametric (SDU) for topological properties of what has been driving the price of renewable energy stock markets and sectors. In this regard, the main object is to define the similarity among sectors in financial market, which is statistically a multivariate time series. The principal mathematical tool to do macro analysis is multivariate vector correlation where multi-dimensional data is considered as a complex system. Furthermore, the base approach for filtering the significant information in a financial system is similarity network analysis. In this paper, the behavior of economic sectors of renewable energy played during 30th July 2015 – 1th January 2018 in America. Results of this study found that, solar sector in renewable energy is confirmed as the dominant sector in America during this period. In addition, results demonstrated that, the leader sector is Solar and the central hubs are Canadian Solar Inc. (CSIQ)from Solar and then Pattern Energy Group Inc. (PEGI)from Solar-Wind sectors.

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Section: Network Construction Of Sectorsmentioning

confidence: 99%

Network Topology of Renewable Energy Companies: Minimal Spanning Tree and Sub-Dominant Ultrametric for the American Stock

Kazemilari

Mohamadi

Mardani

et al. 2019

Technological and Economic Development of Economy

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“…In order to obtain a measure of the goodness of fit between the actual wind data and the regenerated wind data, the correlation function is used. 21 The equation for a multi-dimensional function is given by the equations below:…”

Section: Simulation Modelmentioning

confidence: 99%

Characterization of a two-dimensional static wind field using Radial Basis Functions

et al. 2018

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Radial Basis Functions are a modern way of creating a regression model of a multivariate function when sampled data points are not uniformly distributed in a perfect grid. Radial Basis Functions are well suited to atmospheric characterization when unmanned aerial vehicles (UAVs) are used to sample the given space. Multiple UAVs reduce the time for the Radial Basis Functions to yield a suitable solution to the measured data while data from all aircraft are aggregated and sent to Radial Basis Functions to fit the data. The research presented here focuses on the requirements for a high correlation value between the sampled data and the actual data. It is found that the number of centers is a large driver of the goodness of fit in the Radial Basis Function routine, much like aliasing is an issue in sampling a sinusoidal function. These centers act like a sampling rate for the spatially varying wind field. If the centers are dense enough to fully capture the spatial frequency of the wind field, the Radial Basis Functions will produce a suitable fit. This also requires the number of data points to be larger than the number of centers. The ratio between the number of centers and number of sampled data points declines as the number of centers increases. The results presented here are revealed using a two-dimensional Fourier series analysis coupled to a spatially varying atmospheric wind model and a Radial Basis Function regression model.

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Statistical Inference Concerning Several Redundancy Indices

Lazraq

Cléroux

2001

Journal of Multivariate Analysis

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In this paper we consider a measure of multivariate association between two vectors which generalizes the multiple correlation coefficient and obtain its exact distribution when the parent population is multivariate normal. A test is proposed for the hypothesis that several such measures are zero. This test is an exact test and an explicit expression for its power is obtained. Moreover numerical results are obtained concerning the power of this test in some particular cases. AcademicPress AMS 1991 subject classifications: 62H15; 62E15; 62H20.

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A Multivariate Extension of the Correlation Ratio

Cited by 22 publications

References 4 publications

Network Topology of Renewable Energy Companies: Minimal Spanning Tree and Sub-Dominant Ultrametric for the American Stock

Network Topology of Renewable Energy Companies: Minimal Spanning Tree and Sub-Dominant Ultrametric for the American Stock

Characterization of a two-dimensional static wind field using Radial Basis Functions

Statistical Inference Concerning Several Redundancy Indices

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