knockout_lm: Knock Out Outliers in a Linear Regression
In hkauhanen/hipster: Henri's Idiosyncratic Package for Somewhat Tedious Everyday Routines
Description
Usage
Arguments
Value
Description
Knock out outliers in a linear regression by recursively pruning those
data points that contribute the most to the regression error, operationalized
as the residual sum of squares at each knockout iteration.
Usage
1
knockout_lm(data, formula, id.var)
Arguments
data
Data frame
formula
Regression formula
id.var
Name of identifier variable (column)
Value
Data frame with the following columns:
iterationKnockout iteration
knockeeData pointed knocked out at this iteration
RSS_reductionReduction in residual sum of squares resulting from the knockout
hkauhanen/hipster documentation built on July 4, 2020, 11:25 p.m.
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Description Usage Arguments Value
Description
Knock out outliers in a linear regression by recursively pruning those data points that contribute the most to the regression error, operationalized as the residual sum of squares at each knockout iteration.
Usage
1 | knockout_lm(data, formula, id.var)
|
Arguments
data |
Data frame |
formula |
Regression formula |
id.var |
Name of identifier variable (column) |
Value
Data frame with the following columns:
iterationKnockout iteration
knockeeData pointed knocked out at this iteration
RSS_reductionReduction in residual sum of squares resulting from the knockout
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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