The set of functions used for time series analysis and in forecasting.

A time-series companion package to healthyR

The goal of our analysis was to use different time series methods to predict the oil price for the last 6 months of the data, September 2017 through February 2018, and determine the best prediction model for this data.

This project aims to use World Bank data and analyse it. The objective is to find 10 best countires that deserve the World Bank funding for digital development. This project is completed in collaboration

MATH-342 Time Series course taken at EPFL during Spring 17-18.

Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.

Building a stock price change predictor using shiny in R

Forecast 5 years sales of souvenir data using Holts-winters and ARIMA methods.

This project leverages machine learning techniques in R to analyze and predict stock market trends.

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

Application of real-time visualization and forecasting of COVID-19 build on R and shiny

ARIMA and GARCH modelling

Predicting Amazon Stock Price using ARIMA

ARIMA Time series forecasting to predict inquiry demand using digital advertising data

Assignment codes for Time Series (2020, FGV)

ARIMA model implementation for vehicle`s mileage left until high risk zone and risk of failure prediction using R.

This project is to build an ARIMA model to predict supermarket deals (Coles and Woolworths). It is written in R programming language. The dataset consists of multiple attributes such as date and items name showed on website. The price are updated progressively. The dataset is not having all items, instead only the items of interest.

The purpose of this repository is an end-to-end guide on how to make predictions using ARIMA (SARIMA and SARIMAX), in this case I predicted the volume of bitcoin transactions during 2013 to 2021, achieving satisfactory results.

This repository contains the implementation of the paper "Analysis and forecasting of a time series dataset with an ARIMA model" and presents an analysis and forecasting project for a time series dataset using an AutoRegressive Integrated Moving Average (ARIMA) model. ARIMA is a popular approach for modeling and predicting time series data.

Forecasting monthly US unleaded gas prices using R tidyverts packages