reduce

reduce.editmatrix

reduce.editarray

reduce.editset

Remove variables which are not contained in any edit and remove edits which are 
<code>obviously redundant</code>.

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

reduce function

<dl><dt>E</dt>
<dd><code>editmatrix</code> or <code>editarray</code></dd>
<dt>...</dt>
<dd>arguments to pass to other methods</dd>
<dt>tol</dt>
<dd>elements of <code>E</code> with absolute value &lt; <code>tol</code> are considered 0.</dd></dl>

Arguments

Remove redundant variables and edits. — reduce

<dl>

<dt>E</dt>
<dd><code>editmatrix</code> or <code>editarray</code></dd>


<dt>...</dt>
<dd>arguments to pass to other methods</dd>


<dt>tol</dt>
<dd>elements of <code>E</code> with absolute value &lt; <code>tol</code> are considered 0.</dd>

</dl>

reduce: Remove redundant variables and edits.

Description

Usage

Arguments

See Also