best.reg: Estimate missing morphometric data with a highly correlated...
In LOST: Missing Morphometric Data Simulation and Estimation
Description
Usage
Arguments
Value
Author(s)
References
See Also
Description
Estimates missing morphometric using regression on the most highly correlated morphological variable available
Usage
1
best.reg(x)
Arguments
x
A n X m matrix of morphometric data with n specimens and m variables, containing some percentage of missing values input as NA
Value
Returns a n X m matrix containing both the original morphometric values as well as estimates for all previously missing values.
Author(s)
J. Arbour and C. Brown
References
Brown, C., Arbour, J. and Jackson, D. 2012. Testing of the Effect of Missing Data Estimation and Distribution in Morphometric Multivariate Data Analyses. Systematic Biology 61(6):941-954.
See Also
LOST documentation built on April 14, 2020, 6:18 p.m.
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Description Usage Arguments Value Author(s) References See Also
Description
Estimates missing morphometric using regression on the most highly correlated morphological variable available
Usage
1 | best.reg(x)
|
Arguments
x |
A n X m matrix of morphometric data with n specimens and m variables, containing some percentage of missing values input as NA |
Value
Returns a n X m matrix containing both the original morphometric values as well as estimates for all previously missing values.
Author(s)
J. Arbour and C. Brown
References
Brown, C., Arbour, J. and Jackson, D. 2012. Testing of the Effect of Missing Data Estimation and Distribution in Morphometric Multivariate Data Analyses. Systematic Biology 61(6):941-954.
See Also
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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