enforce_nonneg_weights

Softly enforces nonnegativity of a numeric weight vector. Large negative
values are treated as errors, while small negative values
are truncated to zero.

internal

Methods to estimate finite-population parameters under nonresponse that is not missing at
random (NMAR, nonignorable). Incorporates auxiliary information and user-specified response models,
and supports independent samples and complex survey designs via objects from the 'survey' package.
Provides diagnostics and optional variance estimates. For methodological background see
Qin, Leung and Shao (2002) <doi:10.1198/016214502753479338> and Riddles, Kim and Im (2016) <doi:10.1093/jssam/smv047>.

Maciej Ber<c4><99>sewicz

NMAR

Estimation under not Missing at Random Nonresponse

Maciej Beresewicz

Igor Kołodziej

Mateusz Iwaniuk

enforce_nonneg_weights function

<dl><dt>weights</dt>
<dd>numeric vector of weights.</dd>
<dt>tol</dt>
<dd>numeric tolerance below which negative values are treated as
numerical noise and clipped to zero.</dd></dl>

Arguments

Enforce nonnegativity of weights — enforce_nonneg_weights

<dl>

<dt>weights</dt>
<dd>numeric vector of weights.</dd>


<dt>tol</dt>
<dd>numeric tolerance below which negative values are treated as
numerical noise and clipped to zero.</dd>

</dl>

enforce_nonneg_weights: Enforce nonnegativity of weights

Description

Usage

Value

Arguments

Details