Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets

Simple python example on how to use ARIMA models to analyze and predict time series.

Timeseries for everyone

基于ARIMA时间序列的销量预测模型，实际预测准确率达90%以上，内含有测试记录和实际上线效果。

Time Series Analysis and Forecasting in Python

Projetos de modelagem e previsão de séries temporal em linguagem Python e linguagem R. Usarei vários modelos de bibliotecas e pacotes usados para tratamento, modelagem e previsão de séries temporais. Falarei um pouco sobre cada uma delas, gerarei a validação e as previsões e, por fim, realizarei a avaliação com a métricas pertinentes.

Jupyter Notebooks Collection for Learning Time Series Models

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

Performed time series analysis using ARIMA model in python on online retail dataset.

Creating a model to analyze and predict the trend of the prices of gold.

Mathematical modeling for finantial time series data

Source code for predicting Blood Glucose Concentration

LSTM for time series forecasting

Advanced stock market view

PhD Thesis: "Data Science in the Modeling and Forecasting of Financial Timeseries: from Classic methodologies to Deep Learning"

A collection of notebooks and different prediction models that can predict the stock prices. Also a comparison of how all these models performed.

Forecasting Monthly Sales of French Champagne - Perrin Freres

Companion and Download Site for the SAS Press Book "Applying Data Science - Business Case Studies Using SAS"

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.

Time Series Analysis for Oil Price Prediction