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ARIMA Models in R
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Korshub's take
Mastering Time Series Forecasting
This beginner-friendly course provides a structured path toward mastering ARIMA modeling using the R programming language. By moving from theoretical concepts to practical application, you will learn how to handle both simulated and real-world datasets.
What You Will Learn
- Foundational Analysis: Explore the unique characteristics of time series data using the R stats package.
- Model Fitting: Learn to fit ARMA and integrated ARIMA models using the astsa package.
- Validation & Forecasting: Master the techniques required to check model validity and generate accurate forecasts.
- Seasonal Data: Extend your skills to handle seasonal patterns within your time series data.
Perfect for those looking to build a technical foundation in statistical forecasting through hands-on R implementation.
About this course
In this course, you will become an expert in fitting ARIMA models to time series data using R. First, you will explore the nature of time series data using the tools in the R stats package. Next, you learn how to fit various ARMA models to simulated data (where you will know the correct model) using the R package astsa. Once you have mastered the basics, you will learn how to fit integrated ARMA models, or ARIMA models to various real data sets. You will learn how to check the validity of an ARIMA model and you will learn how to forecast time series data. Finally, you will learn how to fit ARIMA models to seasonal data, including forecasting using the astsa package.
Access
SubscriptionIncluded with a DataCamp subscription
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