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  "body": "\n## Summary\n\nThe Box–Jenkins method is an iterative procedure for building an [[ARIMA model|KTDVZP4DF2]] of a time series and using it to forecast.\nIt cycles through model identification, parameter estimation and diagnostic checking until the fitted model describes the data adequately.\nGeorge Box and Gwilym Jenkins set it out in their 1970 book *Time Series Analysis: Forecasting and Control*.\n\n## Explanations\n\n### L1 human\n\nThe method is a recipe a forecaster follows step by step.\nFirst, look at plots of the data and of its autocorrelations to guess a simple model.\nSecond, fit that model to the data.\nThird, check whether what the model leaves unexplained looks like pure noise; if not, go back and try another model.\nFor example, a sample partial autocorrelation that cuts off after lag $2$ suggests trying an AR($2$) model.\n",
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