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comparison linear_regression.xml @ 1:2e7bc1bb2dbe draft default tip

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author iuc
date Fri, 09 Jan 2015 12:56:07 -0500
parents ffcdde989859
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0:ffcdde989859 1:2e7bc1bb2dbe
3 <expand macro="requirements" /> 3 <expand macro="requirements" />
4 <macros> 4 <macros>
5 <import>statistic_tools_macros.xml</import> 5 <import>statistic_tools_macros.xml</import>
6 </macros> 6 </macros>
7 <command interpreter="python"> 7 <command interpreter="python">
8 linear_regression.py 8 <![CDATA[
9 linear_regression.py
9 $input1 10 $input1
10 $response_col 11 $response_col
11 $predictor_cols 12 $predictor_cols
12 $out_file1 13 $out_file1
13 $out_file2 14 $out_file2
14 1>/dev/null 15 1>/dev/null
16 ]]>
15 </command> 17 </command>
16 <inputs> 18 <inputs>
17 <param format="tabular" name="input1" type="data" label="Select data" help="Dataset missing? See TIP below."/> 19 <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" numerical="True"/> 20 <param name="response_col" label="Response column (Y)" type="data_column" data_ref="input1" numerical="True"/>
19 <param name="predictor_cols" label="Predictor columns (X)" type="data_column" data_ref="input1" numerical="True" multiple="true" > 21 <param name="predictor_cols" label="Predictor columns (X)" type="data_column" data_ref="input1" numerical="True" multiple="true" >
32 <output name="out_file1" file="regr_out.tabular"/> 34 <output name="out_file1" file="regr_out.tabular"/>
33 <output name="out_file2" file="regr_out.pdf"/> 35 <output name="out_file2" file="regr_out.pdf"/>
34 </test> 36 </test>
35 </tests> 37 </tests>
36 <help> 38 <help>
39 <![CDATA[
37 40
38 41
39 .. class:: infomark 42 .. class:: infomark
40 43
41 **TIP:** If your data is not TAB delimited, use *Edit Datasets-&gt;Convert characters* 44 **TIP:** If your data is not TAB delimited, use *Edit Datasets->Convert characters*
42 45
43 ----- 46 -----
44 47
45 .. class:: infomark 48 .. class:: infomark
46 49
47 **What it does** 50 **What it does**
48 51
49 This tool uses the 'lm' function from R statistical package to perform linear regression on the input data. It outputs two files, one containing the summary statistics of the performed regression, and the other containing diagnostic plots to check whether model assumptions are satisfied. 52 This tool uses the 'lm' function from R statistical package to perform linear regression on the input data. It outputs two files, one containing the summary statistics of the performed regression, and the other containing diagnostic plots to check whether model assumptions are satisfied.
50 53
51 *R Development Core Team (2009). 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.* 54 *R Development Core Team (2009). 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.*
52 55
53 ----- 56 -----
54 57
66 - R-squared: the fraction of variance explained by the model 69 - R-squared: the fraction of variance explained by the model
67 - Adjusted R-squared: the above R-squared statistic adjusted, penalizing for the number of the predictors (p) 70 - Adjusted R-squared: the above R-squared statistic adjusted, penalizing for the number of the predictors (p)
68 - p-value: p-value for the t-test of the null hypothesis that the corresponding slope is equal to zero against the two-sided alternative. 71 - p-value: p-value for the t-test of the null hypothesis that the corresponding slope is equal to zero against the two-sided alternative.
69 72
70 73
74 ]]>
71 </help> 75 </help>
72 </tool> 76 </tool>