The set of functions used for time series analysis and in forecasting.
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Updated
Oct 1, 2024 - R
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
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
MATH-342 Time Series course taken at EPFL during Spring 17-18.
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)
Forecasting monthly US unleaded gas prices using R tidyverts packages
Forecasting TLKM stock price with ARIMA model using R Software
ISI Summer Internship
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.
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