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comparison partialR_square.xml @ 0:88ef41de020d draft default tip

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Imported from capsule None
author devteam
date Tue, 01 Apr 2014 10:52:23 -0400
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1 <tool id="partialRsq" name="Compute partial R square" version="1.0.0">
2 <description> </description>
3 <requirements>
4 <requirement type="package" version="2.11.0">R</requirement>
5 <requirement type="package" version="1.7.1">numpy</requirement>
6 <requirement type="package" version="1.0.3">rpy</requirement>
7 </requirements>
8 <command interpreter="python">
9 partialR_square.py
10 $input1
11 $response_col
12 $predictor_cols
13 $out_file1
14 1>/dev/null
15 </command>
16 <inputs>
17 <param format="tabular" name="input1" type="data" label="Select data" help="Dataset missing? See TIP below."/>
18 <param name="response_col" label="Response column (Y)" type="data_column" data_ref="input1" />
19 <param name="predictor_cols" label="Predictor columns (X)" type="data_column" data_ref="input1" multiple="true">
20 <validator type="no_options" message="Please select at least one column."/>
21 </param>
22 </inputs>
23 <outputs>
24 <data format="input" name="out_file1" metadata_source="input1" />
25 </outputs>
26 <requirements>
27 <requirement type="python-module">rpy</requirement>
28 </requirements>
29 <tests>
30 <!-- Test data with vlid values -->
31 <test>
32 <param name="input1" value="regr_inp.tabular"/>
33 <param name="response_col" value="3"/>
34 <param name="predictor_cols" value="1,2"/>
35 <output name="out_file1" file="partialR_result.tabular"/>
36 </test>
37
38 </tests>
39 <help>
40
41 .. class:: infomark
42
43 **TIP:** If your data is not TAB delimited, use *Edit Datasets-&gt;Convert characters*
44
45 -----
46
47 .. class:: infomark
48
49 **What it does**
50
51 This tool computes the Partial R squared for all possible variable subsets using the following formula:
52
53 **Partial R squared = [SSE(without i: 1,2,...,p-1) - SSE (full: 1,2,..,i..,p-1) / SSE(without i: 1,2,...,p-1)]**, which denotes the case where the 'i'th predictor is dropped.
54
55
56
57 In general, **Partial R squared = [SSE(without i: 1,2,...,p-1) - SSE (full: 1,2,..,i..,p-1) / SSE(without i: 1,2,...,p-1)]**, where,
58
59 - SSE (full: 1,2,..,i..,p-1) = Sum of Squares left out by the full set of predictors SSE(X1, X2 … Xp)
60 - SSE (full: 1,2,..,i..,p-1) = Sum of Squares left out by the set of predictors excluding; for example, if we omit the first predictor, it will be SSE(X2 … Xp).
61
62
63 The 4 columns in the output are described below:
64
65 - Column 1 (Model): denotes the variables present in the model
66 - Column 2 (R-sq): denotes the R-squared value corresponding to the model in Column 1
67 - Column 3 (Partial R squared_Terms): denotes the variable/s for which Partial R squared is computed. 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.
68 - Column 4 (Partial R squared): denotes the Partial R squared value corresponding to the variable/s in Column 3. A '-' in this column indicates that the model in Column 1 is the Full model.
69
70 *R Development Core Team (2010). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.*
71
72 </help>
73 </tool>