Trend And PeAkS (TAPAS) analysis of temporal series (e.g. paleoecological records) to assess long-term trend and detect events (and eventually estimate event-return intervals)

Visualization and ANalysis of timE SerieS dAta - Drosophila Activity Monitors

Experimental R interface for ReservoirPy

GARCH and EVT

Climate Variability Indices for Ecological Modelling

R code for the paper 'Forecasting seasonal time series data: a Bayesian model averaging approach'

Bayesian analysis and forecasting of Bitcoin volatility and definition of GARCH and ARCH models through MCMC sampling.

Practicum for MS in Data Science, Regis University, Summer 2020

Univariate Trend Fitting Algorithm

Time Series Analysis for GDP of Canada, the UK and Japan. Attached is the full paper on the economic transformations of these three countries and their GDP over the course of several years.

Project in R to get spot price history data from aws and predict the spot pricing for the current day.

This is the repository for CKME136 Ryerson Big Data Certificate

Shiny dashboard used for analyzing and forecasting fictious data with time series methods (ARIMA and Linear Regression).

The project involves the analysis and forecasting of time series on financial data.

This project covers both Simple Linear Regression and Multiple Linear Regression which are used in prediction airline flight ticket. Moreover, Correlation analysis and Timeseries analysis are performed as well. This project is built as a fulfillment for my masters degree.

2019.02.21 우수상 롯데그룹 온라인 쇼핑몰의 온라인 행동데이터를 이용하여 온라인 선호지수 및 주요 상품군별 수요트렌드 예측

Machine learning is a branch of computer science that studies the design of algorithms that can learn. Typical machine learning tasks are concept learning, function learning or “predictive modeling”, clustering and finding predictive patterns. These tasks are learned through available data that were observed through experiences or instructions.

A Statistical Approach to Understanding the Unemployment Situation Among European Countries from the Reformation and Development Perspective