CovarianceWithMissing: Estimate covariance when data is missing
In FastImputation: Learn from Training Data then Quickly Fill in Missing Data
View source: R/CovarianceWithMissing.R
CovarianceWithMissing R Documentation
Estimate covariance when data is missing
Description
Ignoring missing values can lead to biased estimates of the covariance.
Lounici (2012) gives an unbiased estimator when the data has missing values.
Usage
CovarianceWithMissing(x)
Arguments
x
matrix or data.frame, data with each row an observation and each column a variable.
Value
matrix, unbiased estimate of the covariance.
Author(s)
Stephen R. Haptonstahl srh@haptonstahl.org
References
High-dimensional covariance matrix estimation with missing observations.
Karim Lounici. 2012.
FastImputation documentation built on Sept. 25, 2023, 5:06 p.m.
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View source: R/CovarianceWithMissing.R
| CovarianceWithMissing | R Documentation |
Estimate covariance when data is missing
Description
Ignoring missing values can lead to biased estimates of the covariance. Lounici (2012) gives an unbiased estimator when the data has missing values.
Usage
CovarianceWithMissing(x)
Arguments
x |
matrix or data.frame, data with each row an observation and each column a variable. |
Value
matrix, unbiased estimate of the covariance.
Author(s)
Stephen R. Haptonstahl srh@haptonstahl.org
References
High-dimensional covariance matrix estimation with missing observations. Karim Lounici. 2012.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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