Estimated Marginal Means and Marginal Effects from Regression Models for ggplot2
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Updated
May 22, 2024 - R
Estimated Marginal Means and Marginal Effects from Regression Models for ggplot2
Extending broom for time series forecasting
An integrated framework in R for textual sentiment time series aggregation and prediction
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R package for fitting joint models to time-to-event data and multivariate longitudinal data
Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood
Code repository for the manuscript 'Validation of the performance of competing risks prediction models: a guide through modern methods' (published in BMJ)
Nonparametric regression and prediction using the highly adaptive lasso algorithm
Solution for ENS - Societe Generale Challenge (1st place).
Machine learning pipelines for R.
Functions to analyse compositional data and produce confidence intervals for relative increases and decreases in the compositional components
Applied Predictive Modeling with caret
Exercises From Book "Applied Predictive Modeling" by "Kuhn and Johnson (2013)"
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Package to genomic prediction focused on GE genomic models
This is Repository in which I will upload projects done in MTH 686 A in IIT Kanpur . The course instructor is our favorite and respected Sir Debashis Kundu
The specific problem in this project is about the time-series data trend prediction. The specific application scenario is in e-commerce. You are given a real dataset obtained from a real-world e-commerce application where there were 1000 products and 31490 customers (i.e., buyers) who bought these products. Of these 1000 products there are 100 k…
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