get_variable_t

Generate more specific variable names

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

get_variable_t function

<dl><dt>model_table</dt>
<dd><code>tibble</code>/ <code>data.frame</code> as created in the <code>build_model_table</code> function</dd>
<dt>excl_intercept</dt>
<dd>Boolean to specify whether to drop the "(Intercept)" row of the model table</dd>
<dt>excl_dup</dt>
<dd>Boolean to specify whether to drop the duplicated rows of the model table</dd>
<dt>excl_blanks</dt>
<dd>Boolean to specify whether to drop the blank rows of the model</dd>
<dt>trans_df</dt>
<dd><code>data.frame</code> defining the non-linear transformations</dd></dl>

Arguments

get_variable_t — get_variable_t

<dl>

<dt>model_table</dt>
<dd><code>tibble</code>/ <code>data.frame</code> as created in the <code>build_model_table</code> function</dd>


<dt>excl_intercept</dt>
<dd>Boolean to specify whether to drop the "(Intercept)" row of the model table</dd>


<dt>excl_dup</dt>
<dd>Boolean to specify whether to drop the duplicated rows of the model table</dd>


<dt>excl_blanks</dt>
<dd>Boolean to specify whether to drop the blank rows of the model</dd>


<dt>trans_df</dt>
<dd><code>data.frame</code> defining the non-linear transformations</dd>

</dl>

get_variable_t: get_variable_t

Description

Usage

Value

Arguments

Details

Examples