Homework 2 for the INTL 601 Quantitative Research Methods Course, Prof. David Carlson, Koç University.
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Updated
Mar 28, 2022 - R
Homework 2 for the INTL 601 Quantitative Research Methods Course, Prof. David Carlson, Koç University.
A final project carried out at the African Institute for Mathematical Sciences, AIMS.
Machine Learning: Group Project
A pair of scripts that contain profound statistical analyses. The first one approaches a linear model, while the second one a generalized linear model
Generalized linear models 1 coursework
Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning
This project looks at hurricane data to determine if the femininity level of hurricane name is associated with more deaths.
Study on community compensatory trend, as well as positive and negative density dependence enacting on seedling recruitment in the Dipterocarpaceae
This repository documents my senior year independent project related to exploring the impact of behavioral interactions on the foraging success/attempts of five, peruvian army-ant following birds.
🎓 Tidy regression tools for academics
High Throughput Light Weight Regularized Regression Modeling for Molecular Data
Our team GMT+8 analyzed the given data and recommended which manufacturers MM&A team should partner with to pilot the digital ad program. I utilised my knowledge of the R language to build the statistical prediction model for quantifying the effectiveness of the coupon promotion by the manufacturers in the supermarket.
This repository contains the R code done in the laboratories during the first course of statistical models.
The aim of the GLMM Project is to build general linear (mixed) models that predicts the total number of medals won by countries. GLMs and GLMMs are examined in the Part 1 and Part 2 respectively. Refer to memos in pdf files for details.
Constrained likelihood estimation and inference with truncated lasso penalty for linear, generalized linear, and Gaussian graphical models.
R package: Linear Splines with Convenient Parameterizations
In this repository you can find the code to deal with statistical problems using R. You will find GLM, GLMM
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