apply_normalisation

An interface to accelerate linear regression (Ordinary least squares) modelling, which
allows users to build models quickly, while automatically generating interactive visualizations of the results.
Non-linear models specification (e.g. y = b1*x1 + b2*log(x2)) can be easily constructed using user-defined transformations.
Functions for testing wide ranges of model specifications (e.g. y = b*log(x,10) , y = b*log(x,20) , ...), all at once, are also available.
Finally, models can be imported and exported as Excel files where all the information necessary for re-running the models is stored in separate sheets.

Claudio Paladini

linea

Linear Regression Interface

apply_normalisation function

<dl><dt>raw_data</dt>
<dd><code>data.frame</code> containing data for analysis</dd>
<dt>pool_var</dt>
<dd>string specifying the pool variable name (e.g. 'country')</dd>
<dt>dv</dt>
<dd>string specifying the dependent variable name</dd>
<dt>verbose</dt>
<dd>A boolean to specify whether to print warnings</dd></dl>

Arguments

apply_normalisation — apply_normalisation

<dl>

<dt>raw_data</dt>
<dd><code>data.frame</code> containing data for analysis</dd>


<dt>pool_var</dt>
<dd>string specifying the pool variable name (e.g. 'country')</dd>


<dt>dv</dt>
<dd>string specifying the dependent variable name</dd>


<dt>verbose</dt>
<dd>A boolean to specify whether to print warnings</dd>

</dl>

apply_normalisation: apply_normalisation

Description

Usage

Value

Arguments

Details

Examples