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- Covariance_mapping abstract "In statistics, covariance mapping is an extension of the covariance concept from random variables to random functions. Normal covariance is a scalar (a single number) that measures statistical relation between two random variables. Covariance maps are matrices (arrays of numbers) that show statistical relations between different regions of random functions. Statistically independent regions of the functions show up on the map as zero-level flatland, while positive or negative correlations show up, respectively, as hills or valleys.".
- Covariance_mapping thumbnail Schematics_of_LCLS_covariance_mapping_experiment.png?width=300.
- Covariance_mapping wikiPageID "42572211".
- Covariance_mapping wikiPageRevisionID "606439538".
- Covariance_mapping subject Category:Covariance_and_correlation.
- Covariance_mapping subject Category:Fields_of_application_of_statistics.
- Covariance_mapping subject Category:Molecular_physics.
- Covariance_mapping subject Category:Photochemistry.
- Covariance_mapping subject Category:Quantum_chemistry.
- Covariance_mapping subject Category:Signal_processing.
- Covariance_mapping comment "In statistics, covariance mapping is an extension of the covariance concept from random variables to random functions. Normal covariance is a scalar (a single number) that measures statistical relation between two random variables. Covariance maps are matrices (arrays of numbers) that show statistical relations between different regions of random functions.".
- Covariance_mapping label "Covariance mapping".
- Covariance_mapping sameAs m.010gmypy.
- Covariance_mapping sameAs Q17008005.
- Covariance_mapping sameAs Q17008005.
- Covariance_mapping wasDerivedFrom Covariance_mapping?oldid=606439538.
- Covariance_mapping depiction Schematics_of_LCLS_covariance_mapping_experiment.png.
- Covariance_mapping isPrimaryTopicOf Covariance_mapping.
