Data Estimation using Weighted Averages of Multiple Regressions

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Description

For multivariate datasets, this function enables the estimation of missing data using the Weighted AVERage of all possible Regressions using the data available as performed by Sears et al (2008).

Usage

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waverr(RawData, Nrepeats)

Arguments

RawData

A dataframe with each individual represented by a separate row and each variable by a column. Missing data coded as NA.

Nrepeats

The number of repeats performed for the estimation of the error associated with reconstructed data.

Value

ReconstructedData

A matrix of the original data with the missing data replaced by estimated values. It is also saved as a text file in the working directory as "ReconsructedData.txt".

ReconstructedDataStDev

A matrix of the standard deviation associated with each estimated value. It is also saved as a text file in the working directory as "ReconsructedDataStDev.txt".

ResampledData

A three-dimensional array in which each estimated value is resampled (number of repeats determined by Nrepeats) according to a normal distribution. It is also saved as a text file in the working directory as "ResampledReconstructions.txt".

VariableStDev

A matrix of the error associated with each estimated data point as a function of the standard deviation of Nrepeat resampled estimations. It is also saved as a text file in the working directory as "ResampledReconstructionsStandardDeviation.txt".

Author(s)

Olivia Cheronet, John A. Finarelli

References

Sears, K.E., Finarelli, J.A., Flynn, J.J., & Wyss, A.R. (2008). Estimating body mass in New World "monkeys" (Platyrrhini, Primates), with a consideration of the Miocene platyrrhine, Chilecebus carrascoensis. American Museum Novitates, 3617, 1-29.

Examples

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AllIrisMeasurements<-iris[,1:4]
Xremove<-sample(1:150, 20,replace=TRUE)
Yremove<-sample(1:4, 20,replace=TRUE)
AllIrisMeasurementsWithNA<-AllIrisMeasurements
for (i in 1:20){AllIrisMeasurementsWithNA[Xremove[i],Yremove[i]]<-NA}
waverr(RawData=AllIrisMeasurementsWithNA,Nrepeats=100)

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