Description Usage Arguments Details Value Examples
The main olr() runs all of the possible linear regression equation combinations, which are all of the combinations of dependent variables respect to the independent variable. In essence, the olr() returns the best fit linear regression model. The user can prompt the olr() to return either the best fit statistical summary of either the greatest adjusted Rsquared, or the greatest Rsquared term. Rsquared increases with the addition of an explanatory variable whether it is 'significant' or not, thus this was developed to eliminate that conundrum. Adjusted Rsquared is preferred to overcome this phenomenon, but each combination will still produce different results and this will return the best one.
1 2 3 4 5 6 7 8 9 10 11 12  olr(dataset, responseName = NULL, predictorNames = NULL,
adjr2 = TRUE)
olrmodels(dataset, responseName = NULL, predictorNames = NULL)
olrformulas(dataset, responseName = NULL, predictorNames = NULL)
olrformulaorder(dataset, responseName = NULL, predictorNames = NULL)
adjr2list(dataset, responseName = NULL, predictorNames = NULL)
r2list(dataset, responseName = NULL, predictorNames = NULL)

dataset 
is defined by the user and points to the name of the dataset that is being used. 
responseName 
the response variable name defined as a string. For example, it represents a header in the data table. 
predictorNames 
the predictor variable or variables that are the terms that are to be regressed against the 
adjr2 

Complimentary functions below follow the format: function(dataset, responseName = NULL, predictorNames = NULL)
olrmodels: returns the list of models accompanied by the coefficients. After typing in olrmodels(dataset, responseName, predictorNames)
type the desired summary number to the right of the comma in the brackets: [,x]
where x equals the desired summary number. For example, olrmodels(dataset, responseName, predictorNames)[,8]
olrformulas: returns the list of olr() formulas
olrformulasorder: returns the formulas with the predictors (dependent variables) in ascending order
adjr2list: list of the adjusted Rsquared terms
r2list: list of the Rsquared terms
When responseName
and predictorNames
are NULL
, then the first column in the dataset
is set as the responseName
and the remaining columns are the predictorNames
.
A 'Python' version is available at <https://pypi.org/project/olr>.
The regression summary for the adjusted Rsquared or the Rsquared, specified with TRUE
or FALSE
in the olr().
1 2 3 4 5 6 7 8  file < system.file("extdata", "oildata.csv", package = "olr", mustWork = TRUE)
oildata < read.csv(file, header = TRUE)
dataset < oildata
responseName < 'OilPrices'
predictorNames < c('SP500', 'RigCount', 'API', 'Field_Production', 'OperableCapacity', 'Imports')
olr(dataset, responseName, predictorNames, adjr2 = TRUE)

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