Current repository depicts R usability for time series modeling. Number of scripts represents preprocessing time series, modeling AR, MA, ARIMA with seasonality, ARCH, GARCH, VAR, VECM including statistical testing process and robust check.

Implementation of Time Series

A web-based application for analyzing historical weather data and forecasting future trends using advanced statistical models. Built with Python and Flask, the app provides interactive visualizations, stationarity tests, and predictions using ARIMA and SARIMA models.

Forecasting Wine Sales of Two Different types of Wine. After thorough Data Analysis, different models have been used and tested such as Exponential Smoothing Models, Regression, Naive Forecast, Simple Average, Moving Average. Stationarity of the data is checked. Automated Version of ARIMA/SARIMA Model built. Comparison of Models.

This project presents a dual-phase analysis leveraging Python for two disparate datasets. In the initial segment, an exhaustive time series analysis is conducted on historical weather data sourced from Dublin Airport.

This project deals with Time Series Problem to predict the number of passengers in a train over the next 7 months

Time series preprocessing. (G)ARCH, VECM, VAR modeling on stock data.

Seasonal time-series forecasting of power consumption using SARIMA, with full stationarity diagnostics, ACF/PACF analysis, and interpretable forecasts.

Forecasting_Airline_Passengers_Seats

Predicting Monthly Sales of Perrin Freres Champagne by ARIMA & SARIMAX model.

ARIMA(1,1,1) time series forecasting of U.S. corporate profits after tax (FRED, 1980–2024 Q3) in Stata - ADF stationarity testing, ACF/PACF model selection, Ljung-Box diagnostics, and 16-quarter forecast projecting $4.43T by 2028 Q4.

Time series forecasting project analyzing electricity demand and solar generation using ARIMA modeling, stationarity testing, and autocorrelation analysis to predict energy consumption patterns.

EDA performed on timeseries data and different plots to get insights from data visualizations

Économétrie des séries temporelles : étude de la demande d'électricité en Irlande. Analyse via ACF/PACF et tests de racines unitaires/ruptures (DF, ADF, ZA, LS).

# crime dataset for time series analysis ## Original Source: Chicago Data Portal: Crimes 2001 to Present - Data Description: All Crimes that were reported in the city of Chicago and their details View Preview - Includes: type of crime, exact date/time, lat/long, district/ward, whether there was an arrest, etc.