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)
There is an R version of this package.
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Release files for olr 1.0.6
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| olr-1.0.6-py3-none-any.whl | Python 3 | none | any | Details |
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Release files / olr-1.0.6.tar.gz
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Release files / olr-1.0.6-py3-none-any.whl
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