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>.

Beat Hulliger

modi

Multivariate Outlier Detection and Imputation for Incomplete
Survey Data

Martin Sterchi

Tobias Schoch

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