checkDatamodel

Categorical variables in <code>dat</code> which also occur in <code>E</code> are checked against the datamodel for 
those variables. Numerical variables are checked against edits in <code>E</code> that contain only a single
variable (e.g. \(x &gt; 0\)). Values violating such edits as well as empty values are set to adapt.

Please note: active development has moved to packages 'validate'
and 'errorlocate'. Facilitates reading and manipulating (multivariate) data
restrictions (edit rules) on numerical and categorical data. Rules can be
defined with common R syntax and parsed to an internal (matrix-like format).
Rules can be manipulated with variable elimination and value substitution
methods, allowing for feasibility checks and more. Data can be tested against
the rules and erroneous fields can be found based on Fellegi and Holt's
generalized principle. Rules dependencies can be visualized with using the
'igraph' package.

Edwin Jonge

editrules

Parsing, Applying, and Manipulating Data Cleaning Rules

checkDatamodel function

<dl><dt>E</dt>
<dd>an object of class <code>editset</code>, <code>editarray</code>, or <code>editmatrix</code></dd>
<dt>dat</dt>
<dd>a <code>data.frame</code></dd>
<dt>weight</dt>
<dd>vector of weigths for every variable of <code>dat</code> or an array of weight of the same dimensions as <code>dat</code>.</dd>
<dt>...</dt>
<dd>arguments to be passed to or from other methods</dd></dl>

Arguments

Check data against a datamodel — checkDatamodel

<dl>

<dt>E</dt>
<dd>an object of class <code>editset</code>, <code>editarray</code>, or <code>editmatrix</code></dd>


<dt>dat</dt>
<dd>a <code>data.frame</code></dd>


<dt>weight</dt>
<dd>vector of weigths for every variable of <code>dat</code> or an array of weight of the same dimensions as <code>dat</code>.</dd>


<dt>...</dt>
<dd>arguments to be passed to or from other methods</dd>

</dl>

checkDatamodel: Check data against a datamodel

Description

Usage

Value

Arguments

See Also