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yaImpute (version 1.0-19)

yaImpute: An R Package for k-NN Imputation

Description

Performs nearest neighbor-based imputation using one or more alternative approaches to processing multivariate data. These include methods based on canonical correlation analysis, canonical correspondence analysis, and a multivariate adaptation of the random forest classification and regression techniques of Leo Breiman and Adele Cutler. Additional methods are also offered. The package includes functions for comparing the results from running alternative techniques, detecting imputation targets that are notably distant from reference observations, detecting and correcting for bias, and mapping results.

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Version

Install

install.packages('yaImpute')

Monthly Downloads

4,669

Version

1.0-19

License

GPL (>= 2)

Maintainer

Nicholas Crookston

Last Published

August 9th, 2013

Functions in yaImpute (1.0-19)

rmsd.yai

Root Mean Square Difference between observed and imputed
cor.yai

Correlation between observed and imputed
MoscowMtStJoe

Moscow Mountain and St. Joe Woodlands (Idaho, USA) Tree and LiDAR Data
correctBias

Correct bias by selecting different near neighbors
yaiRFsummary

Build Summary Data For Method RandomForest
plot.notablyDifferent

Plots the scaled root mean square differences
whatsMax

Find maximum column for each row
plot.compare.yai

Plots a compare.yai object
notablyDistant

Find notably distant targets
print.yai

Print a summary of a yai object
foruse

Report a complete imputation
ann

Approximate nearest neighbor search routines
AsciiGridImpute

Imputes/Predicts data for Ascii Grid maps
mostused

Tabulate references most often used in imputation
compare.yai

Compares different k-NN solutions
vars

List variables in a yai object
plot.yai

Plot observed verses imputed data
newtargets

Finds K nearest neighbors for new target observations
notablyDifferent

Finds obervations with large differences between observed and imputed values
unionDataJoin

Combines data from several sources
TallyLake

Tally Lake, Flathead National Forest, Montana, USA
errorStats

Compute error components of k-NN imputations
yai

Find K nearest neighbors
yaiVarImp

Reports or plots importance scores for method randomForest
impute.yai

Impute variables from references to targets