Results 211 to 220 of about 2,491,525 (260)
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Journal of Chemical Education, 1964
The Industrial Operations Simulator was designed to provide a unique method of obtaining suitable data for teaching students with very little statistical background the techniques of data correlation.
Joe D. Cunning +2 more
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The Industrial Operations Simulator was designed to provide a unique method of obtaining suitable data for teaching students with very little statistical background the techniques of data correlation.
Joe D. Cunning +2 more
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Correlation Analysis for Compositional Data
Mathematical Geosciences, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Filzmoser, Peter, Hron, Karel
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Estimating Intraclass Correlation for Binary Data
Biometrics, 1999Summary.This paper reviews many different estimators of intraclass correlation that have been proposed for binary data and compares them in an extensive simulation study. Some of the estimators are very specific, while others result from general methods such as pseudo‐likelihood and extended quasi‐likelihood estimation.
Ridout, Martin S. +2 more
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Data aggregation using spatial and temporal data correlation
2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE), 2015In wireless sensor networks (WSNs), the major challenge for sensor nodes is to send sensed data to sink in an energy efficient way due to limited energy of sensor nodes. Data Aggregation protocols are applied to maximize lifetime of sensor nodes and hence of wireless sensor networks.
Kumar, Sujit, Kumar, Sushil
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Clustering Spatially Correlated Functional Data
2011In this paper we discuss and compare two clustering strategies: a hierarchical clustering and a dynamic clustering method for spatially correlated functional data. Both the approaches aim to obtain clusters which are internally homogeneous in terms of their spatial correlation structure. With this scope they incorporate the spatial information into the
ROMANO, Elvira, MATEU J, GIRALDO R.
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2000
Multivariate count data are likely to have a non-trivial correlation structure. For instance, omitted variables may simultaneously affect more than one count. The modeling of the correlation structure is important for the efficiency of the estimator and the computation of correct standard errors, i.e., valid inference.
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Multivariate count data are likely to have a non-trivial correlation structure. For instance, omitted variables may simultaneously affect more than one count. The modeling of the correlation structure is important for the efficiency of the estimator and the computation of correct standard errors, i.e., valid inference.
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Canonical Correlations with Fallible Data
Psychometrika, 1964The technique of canonical correlation may be used to determine the extent to which two sets of measurements reflect the same underlying traits. However, if the two sets are not perfectly reliable, the unreliability may obscure the fact that they are essentially dependent on similar processes.
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