This repository contains Python functions for predicting time series.

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

velocity.py reads in GROMACS trr trajectory (that inclides velocity information) and calculates center of mass translational velocity and angular velocity. It also computes translational and rotational kinetic energies, temperatures, velocity autocorrelation functions and power spectra

Forecast the Airlines Passengers and CocaCola Prices data set. Prepare a document for model explaining. How many dummy variables you have created and RMSE value for model. Finally which model you will use for Forecasting.

Time Series Forecasting: City and Resort Hotels Bookings forecasting

Codes for calculation of temporal correlations in model-data differences, creating and fitting mathematical models, and cross-validating the fits.

Explored a decade of CPI and BER data using Python and Jupyter notebooks for in-depth time series analysis, forecasting, and error evaluation. Techniques include data cleaning, exploratory analysis, and specialized time series modeling.

Analyze trends and forecast daily revenues.

Exploratory data analysis using python frameworks🎯| Time Series analysis⌚| Regression Analysis🧬

This repository covers essential techniques for time series analysis and forecasting. It covers data manipulation and visualization using Numpy and Pandas, time series analysis with Statsmodels, ARIMA models, deep learning methods like RNNs, LSTM, GRU, etc. and Facebook's Prophet library.

Моделирование реализаций случайного процесса, статистические оценки математического ожидания и дисперсии случайного процесса, статистическая оценка автокорреляционной функции случайного процесса, однородная цепь Маркова, предельные вероятности состояний цепи Маркова, распределение вероятностей состояний цепи Маркова

Time Series Forecasting Methods to forecast Daily Post Publications on Medium

Data Science - Forecasting

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

MATLAB Analysis on Frequency Data of Real World Power Grids

MATLAB codes for analyzing grid simulations for symptoms of Critical Slowing Down.

A research project that addresses the recognition of activities and the gender of the performer using MoVi and MotionSense datasets

Forecasting of Colombian crude oil production using several modeling techniques on this time series

Research case