nz.min

Returns the non-zero non-missing minimum.

internal

Algorithms for multivariate outlier detection when missing values occur.
Algorithms are based on Mahalanobis distance or data depth. Imputation is based
on the multivariate normal model or uses nearest neighbour donors. The algorithms
take sample designs, in particular weighting, into account. The methods are
described in Bill and Hulliger (2016) <doi:10.17713/ajs.v45i1.86>.

Martin Sterchi

modi

Multivariate Outlier Detection and Imputation for Incomplete
Survey Data

Beat Hulliger

nz.min function

<dl><dt>x</dt>
<dd>vector of data.</dd></dl>

Arguments

Author

Non-zero non-missing minimum function — nz.min

<dl>

<dt>x</dt>
<dd>vector of data.</dd>

</dl>

nz.min: Non-zero non-missing minimum function

Description

Usage

Arguments

Author