Distributed Series Forecasting Model: The Key to Time Series Analysis
π Distributed Series Forecasting Model: The Key to Time Series Analysis The distributed series forecasting model is a crucial analytical technique used in various fields such as finance, meteorology, and economics. It is essential for analyzing time-dependent data and predicting future values. In this article, we will explore the concept, types, and applications of distributed series forecasting models in practical scenarios. We will particularly focus on well-known models like ARIMA and GARCH, providing practical tips on how to apply them in data analysis. Even if you're new to time series analysis, don’t worry. By following this article, you will gradually understand even the most complex concepts. Now, let’s dive into the world of distributed series forecasting models together! π Table of Contents π What is a Distributed Series Forecasting Model? π Types of Distributed Series Forecasting Models π ARIMA Model: The Most Commonly Used Predict...