Analyzed a 10-year USD/EUR exchange rate dataset using ARIMA and Exponential Smoothing forecasting models. Achieved a MAPE of approximately 4.68% and RMSE of about 0.0605 for both models.

R source code for my Group Project Essay on Generalised Additive Model

Prediction of customer churn with logistic regression in R. Team project from UPC's Master's Degree in Data Science

A repo of all my baseball analytics projects. Reach me at danielthom18@outlook.com

Analysis of software project costs, identifying key factors that significantly influence effort requirements, through statistical modeling and hypothesis testing.

Predicting PO-SCORAD severity score for eczema using EczemaPred

(Repositório temporário até eu conseguir fazer o upload em forma de pacote propriamente dito). Documentação do pacote poissonINAR1 para Iniciação Cientifica feita em agosto de 2023 à julho de 2024.

R script and documentation of maximum-likelihood estimation for MOI and lineage frequency estimates accounting for incomplete data

Here is a whole bunch of genomic data analyses using Bioconductor packages. The files are found in the form of .R files.

LMS growth chart algorithm

The question-answer paper discusses Data Science Statistical data modeling methods such as Logistic Regression, One-Way and Two-Way ANOVA

Implementation for HMC Math158: Statistical Linear Models

Statistical model to simulate individual haemoglobin concentrations in human hosts as a function of observed egg counts quantifying hookworm infection. The model employs latent variables to reproduce an underlying worm burdens distribution in the population. The model after calibration is used to predict the prevalence of anaemia that can be att…

Case study on regularisation methods for statistics and machine learning

Proofs, Analysis, and Discussion of various Algorithms in Computational Statistics

This project investigates the causal effects of the 2009 Abruzzo earthquake in Italy, with a particular focus on labor market outcomes, household income, and GDP.

Explores the financial landscape of first-generation college students, analyzing patterns in student debt based on factors like median income, net price of attendance, and enrollment size.

Personal R package

🌍 Implement climate prediction models to transform global data into localized forecasts for effective water resource management and impact assessment.