Time series ARIMA models and the NOAA Global Climate at a Glance (1910-2015) : average land temperatures in Asia /
This dataset example introduces researchers to autoregressive integrated moving average (ARIMA) models for a single time series variable. An ARIMA model is a statistical model used to estimate the temporal dynamics of an individual times series. ARIMA models are frequently used for forecasting futur...
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| Format: | eBook |
| Language: | English |
| Published: |
London :
SAGE Publications, Ltd.,
2017.
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| Online Access: | Connect to the full text of the electronic book |
| Summary: | This dataset example introduces researchers to autoregressive integrated moving average (ARIMA) models for a single time series variable. An ARIMA model is a statistical model used to estimate the temporal dynamics of an individual times series. ARIMA models are frequently used for forecasting future values of the time series in question. This example uses a subset of data from the United States National Oceanic and Atmospheric Administration (NOAA) Climate at a Glance website. It examines the temporal dynamics in average annual land temperatures in Asia from 1910 to 2015. Understanding trends in global temperature will help researchers and policy makers better understand potential climate change and plan for its impact. The sample dataset used for this example has been cleaned and organized to make this example easier to follow. Interested readers should read the full documentation for the dataset before using it for research (http://www.ncdc.noaa.gov/cag/time-series/global).Direct Prerequisites: Time Series ACFs and PACFs. |
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| Physical Description: | 1 online resource : illustrations |
| ISBN: | 9781473995321 1473995329 |