Nearest Neighbor Observation Imputation and Evaluation Tools

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, bootstrapping and building ensemble imputations, and mapping results.


News

Changes in version 1.0-31:

  • Changed a variable name in one of the ANN routines so that the code can compile on Solaris. Removed an unused variable in the ANN routines.

Changes in version 1.0-30:

  • Removed the c++ "register" keyword from the ann sources as requested by CRAN.
  • Added method="gower" for gower distance that allows categorical variables in the X data (the Y data are ignored, analogous to method="raw" where the relationship between the X and Y data are not relevant).
  • Fixed a bug in varSelection pointed out by Francisco Mauro.

Changes in version 1.0-27 and 1.0-29:

  • Addressed an issue in the ann source code (likely a false positive) found by rchk at CRAN.
  • Added RegisteredNativeSymbol usage according to best practices
  • The error when bootstraping with method="randomForests" is fixed.
  • Fixed an error in yai() when it is called by varSelection() using yaiMethod="randomForest", thanks to Andrew Haywood.

Changes in version 1.0-25 and 1.0-26:

  • Added import directives to meet recent CRAN rules that say that functions from default packages other than base which are used in the package code need to be imported.

Changes in version 1.0-24:

  • Changed the examples for several functions so that they run even when dependent packages are not present.
  • Changed package title to comply with CRAN rules
  • Changed require to requireNamespace in errorstats.R
  • Fixed error in AsciiGridImpute insuring that factors are correctly output and that the legend is accurate.
  • Fixed url to a citation thanks to RForge checks!
  • Added the ability to pass ... to impute() it is called by AsciiGridImpute().
  • Made several changes to conform to the instructions regarding the use of "requireNamespace" for "suggested" packages.
  • Modified how reference observations are delt with when bootstrapping. Now, a reference that has been selected more than once due to sampling with replacement can not be used to represent itself unless options are used to force that behavior. Prior to this change, a reference could be used to represent itself when it existed more than once in the bootstrap sample causing deflated error estimates. Thanks to Patrick Fekety for pointing the problem and doing most of the work that lead to a solution.

Changes in version 1.0-23:

  • Added package parallel to the suggested list in DESCRIPTION, issue reported by RForge checks.
  • Fixed a bug in yai() when categorical predictors are used, reported by Nan Pond.
  • Fixed a bug in yai() that was revealed when bootstrapping. Thanks to Jan Rombouts.
  • Enhanced AsciiGridImpute() to trim the number of files being read. Thanks to Nicolas Py.

Changes in version 1.0-22:

  • Greatly improved the speed of impute.R, thanks to Bastien Ferland-Raymond who pointed out the problem.
  • Fixed an error in AsciiGridImpute() pointed out by Nicolas PY.
  • Fixed an error in yai() concerning the specification of mtry when method="randomForest", thanks to Guy Strickland.

Changes in version 1.0-21:

  • Added code to grmsd() so that it "runs" wiht single variables (ie, just one y from lm).
  • Added an argument to yai() that allows one to specify a different subset of X-variables for each Y-variable.
  • Fixed a bug in reporting the results when method="randomForest" and the rfmethod="regression".
  • Fixed two long-standing bugs in AsciiGridImpute and AsciiGridPredict. One was that the output grid headers would not be output correctly when the nodata argument was used and the other delt with a problem when predict returned a matrix.
  • Modified the examples in AsciiGridImpute so that they use a tempdir() for output files.
  • Added the use of grmsd() in the examples in yai().
  • Fixed return value in grmsd() when argument rtnVectors is TRUE

Changes in version 1.0-20:

  • Added varSelection() to aid in variable selection. A plot function is include to aid in understanding the results; bestVars() returns what seem to be a set of "best" variables for objects created by varSelection().
  • Added grmsd() to compute a generalized root mean square error which is a Mahalanobis distance between observed and imputed. Provides a single score useful for ranking imputation models and methods (or returns vectors of distances).
  • Added rmsd(); it is an alias to rmsd.yai().
  • Added method="median" to function impute.
  • Added method="msnPP" to function yai to enable using canonical correlation via projection pursuit from package ccaPP
  • Added ensembleImpute() to get an mean or median imputation for several separate imputations. Computes the mode for factors.
  • Added John Coulston as an author on some of the new functions and the package.
  • Added bootstrap= option to yai() so that reference observations can be sampled with replacement forming a bootstrap rep.
  • Added sampleVars= option to yai() so that X-, Y- or both kinds of variables can be sampled.
  • Added buildConsensus() to find a consensus imputation over several reps and forming one yai object.
  • Added (at long last) a predict function.
  • Added the ability to specify the scaling values for rmsd.yai and compare.yai
  • Modified some help files to improve acknowledgments and cross references.
  • Fixed a small typographical error in the help for correctBias(), accomplished minor edits to other help files.
  • Added the ability to specify k in function newtargets (how did I miss that?).
  • Changed the variable importance score calculation for yaiVarImp() from "MeanDecreaseGini" to "MeanDecreaseAccuracy" and made it clear in the help file.
  • Added function applyMask() that removes (or keeps) reference neighbors that share group membership with a target. Thanks to Clara Antón Fernández for suggestions that lead to this function being added.
  • Small update to the COPYRIGHTS file to make clear that Andrew O. Finley wrote annImpute.cpp

Changes in version 1.0-19:

  • Moved COPYRIGHTS to inst/COPYRIGHTS and greatly added detailed information to the file.
  • Modified DESCRIPTION to note contribution of the authors of ANN (as per policy).
  • Added a Copyright statement to DESCRIPTION.
  • Added detail to the Description statement in file DESCRIPTION.
  • Fixed print.yai.R error when there is only one target and K>1.
  • Modified the file handling in AsciiGridPredict (and AsciiGridImpute).
  • Fixed a case where a reference picks itself as the second most similar neighbor. This only happens when there are two or more identical reference observations (thanks to Petteri Packalen).
  • Further revision to the ftest to deal with degenerate cases and put in a trap on the use of method="msn2" when there are too few observations.

Changes in version 1.0-18:

  • Added a function (notablyDifferent) to use a consistent method to identify observations with large error.
  • Added an function to (plot.notablyDifferent) to plot the data from notablyDifferent().
  • Modified the ftest in yai() so that it correctly computes the number of canonical variates.

Changes in version 1.0-17:

  • Replaced deprecated calls to sd(|<data.frame>) and mean(|<data.frame>) with apply().
  • Commented out use of cout in ANN routines.
  • Added a function (correctBias) to check for bias and correct it by finding different neighbors.
  • Added an option to notablyDistant() to compute the threshold using quantile().
  • Changed Crookston's email address.

Changes in version 1.0-16:

  • Fixed and moved this news files.
  • Fixed long standing error in the way Mahalanobis distances are computed (thanks to Petteri Packalen)
  • Fixed the use of "useid" in AsciiGridImpute and modified the help pages to make it more clear.
  • Removed the provisional use of a modified versions of randomForest.default as the stock version meets the needs. Also removed, for the same reason, a modified version predict.cca.
  • Removed the long-deprecated "addXlevels" as it is no longer needed with newer versions of randomForest.

Changes in version 1.0-15:

  • The update to ANN headers were reapplied.

Changes in version 1.0-14:

  • Fixed typos in yai.Rd
  • Added to the ability to pick neighbors at random among 1:k nearest in function foruse().
  • Updated ANN headers for newer gcc

Changes in version 1.0-13:

  • Bug fix in unionDataJoin that effects non-yaImpute uses of this function
  • Fixed AsciiGridImpute to better deal with NA's generated when ancillary data are being mapped.
  • Fixed errorStats to deal with case where rmsd can not be computed due to missing data.
  • Added drop=FALSE to deal with case where only one variable is left in the computations of rmsd after variables with no observed values are removed.
  • Fixed some problems in the customized version of randomForest.default to comply with current R coding standards.
  • Same as above for yaiRFSummary.

Changes in version 1.0-12:

  • Not listed.

Changes in version 1.0-11:

  • Not listed.

Changes in version 1.0-10:

  • Not listed.

Changes in version 1.0-9:

  • This NEWS file was started, prior changes were not logged.
  • Fixed error in AsciiGridImpute/AsciiGridPredict when lon/lat argument is used.
  • Improved the help file for AsciiGridImpute/AsciiGridPredict.

Reference manual

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install.packages("yaImpute")

1.0-31 by Nicholas L. Crookston, 5 months ago


Browse source code at https://github.com/cran/yaImpute


Authors: Nicholas L. Crookston , Andrew O. Finley , John Coulston (Sunil Arya and David Mount for ANN)


Documentation:   PDF Manual  


Task views: Official Statistics & Survey Methodology, Missing Data


GPL (>= 2) license


Imports grDevices, graphics, stats, utils

Suggests vegan, ccaPP, randomForest, gam, fastICA, parallel, gower


Imported by ALEPlot, NCSampling, iml, neuroim, spatialEco, stlplus.

Depended on by intrinsicDimension.

Suggested by LICORS.


See at CRAN