print.yai

summary.yai

an object of class <code>yai</code>.

&#8230;

Provides a summary of a <code>yai</code> object, showing the
 call and essential data customized for each method used.

print

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.

Nicholas Crookston

yaImpute

Nearest Neighbor Observation Imputation and Evaluation Tools

print.yai function

<dl> <dt>x</dt>
<dd>an object of class <code>yai</code>.</dd> <dt>...</dt>
<dd>not used</dd></dl>

Arguments

Nicholas L. Crookston <a href="/link/ncrookston.fs%40gmail.com?package=yaImpute&version=1.0-32" data-mini-rdoc="yaImpute::ncrookston.fs@gmail.com">ncrookston.fs@gmail.com</a> 
 Andrew O. Finley <a href="/link/finleya%40msu.edu?package=yaImpute&version=1.0-32" data-mini-rdoc="yaImpute::finleya@msu.edu">finleya@msu.edu</a>

Author

Print a summary of a yai object — print.yai

<dl>

 <dt>x</dt>
<dd>an object of class <code>yai</code>.</dd>

 <dt>...</dt>
<dd>not used</dd>

</dl>

Nicholas L. Crookston <a href='mailto:ncrookston.fs@gmail.com'>ncrookston.fs@gmail.com</a> 
 Andrew O. Finley <a href='mailto:finleya@msu.edu'>finleya@msu.edu</a>

print.yai: Print a summary of a yai object

Description

Usage

Arguments

Author