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Final project of “Statistical Programming with R” course, where I implemented a package to run a logit estimation from scratch.

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avila/logitModel

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logitModel

As part of the Statistical Programming with R course ministered in the Winter Term of 2017 / 2018, the final project was to write a R package from scratch. This pacakge implements an logistic regression estimation via Maximum Likelihood Estimator based on a Newton-Rahpson algorithm. It also includes a formula interface for easier usage, a print, summary and plot S3-Methods that mimics the glm(..., family = binomial) implementation of the stats package as well as a pairs method for an overview of the interaction between the explanatory and explained variables.

Installation

#install.packages("devtools")
devtools::install_github("avila/logitModel")

Vignette

To read the full vignette explaining the package, run from R:

vignette("logitModel")

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Final project of “Statistical Programming with R” course, where I implemented a package to run a logit estimation from scratch.

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