Synthetically produced data are provided to test the FuzzyHRT algorithm.

dataset

The presence of outliers in a dataset can substantially bias the
results of statistical analyses. To correct for outliers, micro edits are
manually performed on all records. A set of constraints and decision rules
is typically used to aid the editing process. However, straightforward
decision rules might overlook anomalies arising from disruption of linear
relationships. Computationally efficient methods are provided to
identify historical, tail, and relational anomalies at the data-entry
level (Sartore et al., 2024; <doi:10.6339/24-JDS1136>). A score statistic
is developed for each anomaly type, using a distribution-free approach
motivated by the Bienaymé-Chebyshev's inequality, and fuzzy logic is used
to detect cellwise outliers resulting from different types of anomalies.
Each data entry is individually scored and individual scores are combined
into a final score to determine anomalous entries. In contrast to fuzzy
logic, Bayesian bootstrap and a Bayesian test based on empirical
likelihoods are also provided as studied by Sartore et
al. (2024; <doi:10.3390/stats7040073>). These algorithms allow for a more
nuanced approach to outlier detection, as it can identify outliers at
data-entry level which are not obviously distinct from the rest of the
data.
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This research was supported in part by the U.S. Department of Agriculture,
National Agriculture Statistics Service. The findings and conclusions in
this publication are those of the authors and should not be construed to
represent any official USDA, or US Government determination or policy.

Luca Sartore

HRTnomaly

Historical, Relational, and Tail Anomaly-Detection Algorithms

Lu Chen

Justin van Wart

Andrew Dau

Valbona Bejleri

toy function

The <code>toy</code> data is a <code>data.frame</code> object consisting of 9265 synthetic records and 5 variables:<dl>
 <dt><code>strata</code></dt>
<dd>a numeric value of the strata</dd> <dt><code>unit_id</code></dt>
<dd>a character string with the record ID</dd> <dt><code>master_varname</code></dt>
<dd>a character string with the names of the variables</dd> <dt><code>current_value_num</code></dt>
<dd>a numeric value with the current synthetic observation</dd> <dt><code>pred_value</code></dt>
<dd>a numeric value with the previously synthetic observation</dd> 
</dl>

Format

Toy dataset — toy

The <code>toy</code> data is a <code>data.frame</code> object consisting of 9265 synthetic records and 5 variables:<dl>
 <dt><code>strata</code></dt>
<dd>a numeric value of the strata</dd>

 <dt><code>unit_id</code></dt>
<dd>a character string with the record ID</dd>

 <dt><code>master_varname</code></dt>
<dd>a character string with the names of the variables</dd>

 <dt><code>current_value_num</code></dt>
<dd>a numeric value with the current synthetic observation</dd>

 <dt><code>pred_value</code></dt>
<dd>a numeric value with the previously synthetic observation</dd>

 
</dl>

toy: Toy dataset

Description

Usage

Arguments

Format

Examples