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Multivariate Regression Shrinkage and Selection by Canonical Correlation Analysis
An, Baiguo - 2012
end, a novel relationship between multivariate regression and canonical correlation is discovered. Subsequently, its …
Persistent link: https://www.econbiz.de/10013096103
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Generalized Correlations and Kernel Causality Using R Package GeneralCorr
Vinod, Hrishikesh D. - 2016
Karl Pearson developed the correlation coefficient r(X,Y) in 1890's. Vinod (2014) develops new generalized correlation …
Persistent link: https://www.econbiz.de/10012991829
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Various versatile variances : an object-oriented implementation of clustered covariances in R
Berger, Susanne; Graham, Nathaniel; Zeileis, Achim - 2017
Clustered covariances or clustered standard errors are very widely used to account for correlated or clustered data, especially in economics, political sciences, or other social sciences. They are employed to adjust the inference following estimation of a standard least-squares regression or...
Persistent link: https://www.econbiz.de/10011697332
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Leverage, influence, and the jackknife in clustered regression models : reliable inference using summclust
MacKinnon, James G.; Nielsen, Morten Ørregaard; Webb, … - 2022
Cluster-robust inference is widely used in modern empirical work in economics and many other disciplines. The key unit of observation is the cluster. We propose measures of "high-leverage" clusters and "influential" clusters for linear regression models. The measures of leverage and partial...
Persistent link: https://www.econbiz.de/10013169182
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A Decomposition Of The Pearson's Correlation Coefficient Into One- And Two-Group Measures
Papadopoulos, Savas - 2022
We reformulate and decompose the Pearson and Spearman correlation coefficients into two components. We recommend the …-parallel line correlation, hidden, mixed, influenced, or weaker but significant relationships not recognized by standard …
Persistent link: https://www.econbiz.de/10014235900
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Testing Covariates in High Dimensional Regression
Lan, Wei - 2013
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically, we employ the partial covariances between the response variable and the tested covariates to obtain a test statistic. The resulting...
Persistent link: https://www.econbiz.de/10013082410
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Matrix Box-Cox models for multivariate realized volatility
Weigand, Roland - 2014
covariance matrix eigenvalues, while for the Box-Cox dynamic correlation (BC-DC) specification the variances are transformed …
Persistent link: https://www.econbiz.de/10010344500
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Testing in high-dimensional spiked models
Johnstone, Iain M.; Onatski, Alexei - 2018
Persistent link: https://www.econbiz.de/10012667588
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Improving the validity of theory testing in logistics research using correlated components regression
Garver, Michael S.; Williams, Zachary - In: International journal of logistics : research and … 21 (2018) 4, pp. 363-377
Persistent link: https://www.econbiz.de/10011881329
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Time-Localized Wavelet Multiple Regression and Correlation : Eurozone Stock Markets Across Scales and Time
Fernandez-Macho, Javier - 2020
regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multi …-scale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard … century. It is shown how the evolution of the correlation structure in these markets has been far from homogeneous both along …
Persistent link: https://www.econbiz.de/10012854086