mlr: Prompt for Regression Modeling
In labarreb/FinalProject: Prompt-Based Functions for Modeling
Description
Usage
Details
Author(s)
Examples
Description
Initialize Prompt-Based Regression Modeling (Description)
Usage
1
mlr()
Details
The user is able to request a type of model
and then input any model options and outputs that he/she
wishes. After a dataset is entered, inputs include: variables,
interaction terms, type of distribution, and type of regression.
Outputs include: summary statistics, plots for diagnostics,
point estimates, and confidence intervals. Basic coin flip
and dice roll functions are included for entertainment. (Details)
Author(s)
c(Brian LaBarre, Silvia Jakubski)
Examples
1
mlr()
labarreb/FinalProject documentation built on May 3, 2019, 1:34 p.m.
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Description Usage Details Author(s) Examples
Description
Initialize Prompt-Based Regression Modeling (Description)
Usage
1 | mlr()
|
Details
The user is able to request a type of model and then input any model options and outputs that he/she wishes. After a dataset is entered, inputs include: variables, interaction terms, type of distribution, and type of regression. Outputs include: summary statistics, plots for diagnostics, point estimates, and confidence intervals. Basic coin flip and dice roll functions are included for entertainment. (Details)
Author(s)
c(Brian LaBarre, Silvia Jakubski)
Examples
1 | mlr()
|
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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