Discover the answers to your questions at Westonci.ca, where experts share their knowledge and insights with you. Our platform offers a seamless experience for finding reliable answers from a network of knowledgeable professionals. Discover detailed answers to your questions from a wide network of experts on our comprehensive Q&A platform.
Sagot :
For the prediction of univariate time series data, Autoregressive Integrated Moving Average, or ARIMA, is one of the most used forecasting techniques.
With examples, define the ARIMA model.
Based on its own historical values, the ARIMA model forecasts a given time series. It can be used to any non-seasonal number series that shows patterns and is not a collection of random occurrences. For instance, sales information from a clothes business would be a time series since it was gathered over time.
Which forecasting approach is more effective for seasonal data?
This approach works best with data that has a pattern and seasonality but does not get stronger with time. As a result, the forecast is curved, highlighting the seasonal fluctuations in the data.
To know more about ARIMA model visit:-
https://brainly.com/question/29589592
#SPJ4
Thank you for trusting us with your questions. We're here to help you find accurate answers quickly and efficiently. Thanks for stopping by. We strive to provide the best answers for all your questions. See you again soon. We're glad you visited Westonci.ca. Return anytime for updated answers from our knowledgeable team.
