🔗 Methods for Correlation Analysis

2D Outlier Analysis using Shiny

Mean and Covariance Matrix Estimation under Heavy Tails

An implementation of Isolation forest

Imputation of Financial Time Series with Missing Values and/or Outliers

Transform Univariate Time Series

RoBTT R package for estimating robust Bayesian t-test

Predicting disease spread, a DrivenData competition. I'am currently participating in this competition. I used it as submission for the second capstone project in the course 'Professional Certificate in Data Science' provided by Harvard University (HarvardX) on EDX.

A beginners tutorial for using R for exploratory analyses

Applied analysis on the Bayesian student-t "Robust" regression model with Jeffrey's prior. Compared its model performance and robustness of posterior distributions with the Gaussian model when outliers are present.

R package as a result of Scout Jarman's URCO grant reaserch.

The HotellingEllipse package helps draw the Hotelling's T-squared ellipse on a PCA or PLS score scatterplot by computing the Hotelling's T-squared statistic and providing the ellipse's coordinates, semi-minor, and semi-major axes lengths.

tsrobprep - an R package for robust preprocessing of time series data. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001084

In this repository, using the statistical software R, are been analyzed robust techniques to estimate multivariate linear regression in presence of outliers, using the Bootstrap, a simulation method where the construction of sample distribution of given statistics occurring through resampling the same observed sample.

EDA is a must to do step in the data science workflow. Working on data, wrangling & transforming them is time consuming, and it determine the success degree of the next steps (pre preocessing, modelling, communicating outputs & decision making). This repo will show you how to perform EDA in R using the tidyverse ecosystem, and will introduce a c…

CU M.Sc. Project

Outlier Detection Using Cluster Analysis

outlier dytection