<tool id="rcve1" name="Compute RCVE" version="1.0.0">
  <description> </description>
  <command interpreter="python">
    rcve.py 
      $input1
      $response_col
      $predictor_cols
      $out_file1
      1>/dev/null
  </command>
  <inputs>
    <param format="tabular" name="input1" type="data" label="Select data" help="Dataset missing? See TIP below."/>
    <param name="response_col" label="Response column (Y)" type="data_column" data_ref="input1" />
    <param name="predictor_cols" label="Predictor columns (X)" type="data_column" data_ref="input1" multiple="true">
        <validator type="no_options" message="Please select at least one column."/>
    </param>
  </inputs>
  <outputs>
    <data format="input" name="out_file1" metadata_source="input1" />
  </outputs>
  <requirements>
    <requirement type="python-module">rpy</requirement>
  </requirements>
  <tests>
    <!-- Test data with vlid values -->
  	<test>
      <param name="input1" value="reg_inp.tab"/>
      <param name="response_col" value="1"/>
      <param name="predictor_cols" value="2,3,4"/>
      <output name="out_file1" file="rcve_out.dat"/>
    </test>
    
  </tests>
  <help>

.. class:: infomark

**TIP:** If your data is not TAB delimited, use *Edit Datasets-&gt;Convert characters*

-----

.. class:: infomark

**What it does**

This tool computes the RCVE (Relative Contribution to Variance) for all possible variable subsets using the following formula:

**RCVE(i) = [R-sq (full: 1,2,..,i..,p-1) - R-sq(without i: 1,2,...,p-1)] / R-sq (full: 1,2,..,i..,p-1)**,
which denotes the case where the 'i'th predictor is dropped. 


In general,
**RCVE(X+) = [R-sq (full: {X,X+}) - R-sq(reduced: {X})] / R-sq (full: {X,X+})**,
where,

- {X,X+} denotes the set of all predictors, 
- X+ is the set of predictors for which we compute RCVE (and therefore drop from the full model to obtain a reduced one), 
- {X} is the set of the predictors that are left in the reduced model after excluding {X+} 


The 4 columns in the output are described below:

- Column 1 (Model): denotes the variables present in the model ({X})
- Column 2 (R-sq): denotes the R-squared value corresponding to the model in Column 1
- Column 3 (RCVE_Terms): denotes the variable/s for which RCVE is computed ({X+}). These are the variables that are absent in the reduced model in Column 1. A '-' in this column indicates that the model in Column 1 is the Full model.
- Column 4 (RCVE): denotes the RCVE value corresponding to the variable/s in Column 3. A '-' in this column indicates that the model in Column 1 is the Full model.
  
  
  </help>
</tool>