A statistical decomposition of internet traffic data (in bits) over time. Using RStudio I performed a Simple Trend Model, Multiplicative Classical Decomposition, Additive Classical Decomposition, and an ARIMA model.

A time-series companion package to healthyR

In this project, this research generally investigates the financial time series such as the price & return of NASDAQ Composite Index using ARIMA and GARCH methods.

Analyze NASDAQ100 stock data. Used ARIMA + GARCH model and machine learning techniques Naive Bayes and Decision tree to determine if we go long or short for a given stock on a particular day

[AI6123] Time Series Analysis is an elective course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6123 of Semester 2, AY2021-2022, starting from 01/2022. The instructor of this course is Prof. Pan Guangming.

R package consisting of functions and tools to facilitate the use of traditional time series and machine learning models to generate forecasts on univariate or multvariate data. Different backtesting scenarios are available to identify the best performing models.

Studies and homework of the Time Series course at FGV EMAp.

Traffic prediction and time-spent estimation in Buenos Aires' toll booths.

Sales Forecast of Automobile Cars using R programming

Predicting Change in GDP of the United States

Methodology and code to use social data for forecasting shortage of essential commodities (gasoline/PPE/toilet paper) during disasters like hurricanes and pandemics

This is a final project for a Time Series course. My professor told me I could further work on it.

The aim of project was to make an app using shiny and R programming to predict the stock prices of various companies for the next 5 days using neural networks and arima model.

ARIMA model for forecasting daily Covid-19 cases in Morocco

Prediction of road casualties and evaluate the impact of transformations in Time Series Modeling and Forecasting with ARIMA using the R programming language

A multivariate time series forecasting of pollution data using ARIMA, LM & ARIMAX in R

Assignment codes for Time Series (2020, FGV)

Economic Time Series Analysis, Prediction and Forecasting using advanced Statistical methods and an ad-hoc estimated ARIMA (SARIMAX) model in R.

Machine learning models build on real time data