The olr function runs all the possible combinations of linear regressions with all of the dependent variables against the independent variable and returns the statistical summary of either the greatest adjusted R-squared or R-squared term.
datasetname = pd.read_csv('C:\Rstuff\olr\inst\extdata\oildata.csv') resvarname = datasetname[['OilPrices']] expvarnames = datasetname[['SP500', 'RigCount', 'API', 'Field_Production', 'RefinerNetInput', 'OperableCapacity', 'Imports', 'StocksExcludingSPR']]
The TRUE or FALSE in the olr function, specifies either the adjusted R-squared or the R-squared regression summary, respectfully.
Adjusted R-squared olr(datasetname, resvarname, expvarnames, adjr2 = "True")
R-squared olr(datasetname, resvarname, expvarnames, adjr2 = "False")
list of summaries olrmodels(datasetname, resvarname, expvarnames)
list of formulas olrformulas(datasetname, resvarname, expvarnames)
list of forumlas with the dependant variables in ascending order olrformulasorder(datasetname, resvarname, expvarnames)
the list of adjusted R-squared terms adjr2list(datasetname, resvarname, expvarnames)
the list of R-squared terms r2list(datasetname, resvarname, expvarnames)
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Release files for olr 0.0.2
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| olr-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Release files / olr-0.0.2-py3-none-any.whl
| Download URL | olr-0.0.2-py3-none-any.whl |
|---|---|
| Size | 14.0 kB |
| Tags | Python 3 |
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