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course

ARIMA Models in R

Intermediate

4.6+

Updated 12/2024

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

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RProbability & Statistics4 hours13 videos45 exercises3,600 XP32,041Statement of Accomplishment

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Course Description

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.

Prerequisites

Time Series Analysis in R

1

Time Series Data and Models

First things first

Elements of time series

Stationarity and nonstationarity

Differencing

Detrending data

Dealing with trend and heteroscedasticity

Stationary time series: ARMA

Simulating ARMA models

2

Fitting ARMA models

AR and MA models

Fitting an AR(1) model

Fitting an AR(2) model

Fitting an MA(1) model

AR and MA together

Fitting an ARMA model

Identify an ARMA model

Model choice and residual analysis

Model choice - I

Model choice - II

Residual analysis - I

Residual analysis - II

ARMA get in

3

ARIMA Models

ARIMA - integrated ARMA

ARIMA - plug and play

Simulated ARIMA

Global warming

ARIMA diagnostics

Diagnostics - simulated overfitting

Diagnostics - global temperatures

Forecasting ARIMA

Forecasting simulated ARIMA

Forecasting global temperatures

4

Seasonal ARIMA

Pure seasonal models

P/ACF of pure seasonal models

Fit a pure seasonal model

Mixed seasonal models

Fit a mixed seasonal model

Data analysis - unemployment I

Data analysis - unemployment II

Data analysis - commodity prices

Data analysis - birth rate

Forecasting seasonal ARIMA

Forecasting monthly unemployment

How hard is it to forecast commodity prices?

Congratulations!

ARIMA Models in R

Course
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Included withPremium or Teams

Don’t just take our word for it

*4.6

from 16 reviews

75%

13%

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Most recent
Top reviews

Huda G.

about 1 month

Contents delivered in a concise way. The course is focused and informative. I highly recommend mastering time series skills on datacamp.

Bruce J.

4 months

It was easy to understand and covered important concepts well.

Nurilla A.

9 months

Nice!

Olajide O.

10 months

Excellently and clearly explained

Peter G.

about 1 year

d

"Contents delivered in a concise way. The course is focused and informative. I highly recommend mastering time series skills on datacamp."

Huda G.

"It was easy to understand and covered important concepts well."

Bruce J.

"Nice!"

Nurilla A.

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