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@ -363,7 +363,7 @@ as your buckets:
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"buckets_path": "the_sum",
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"window" : 30,
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"model" : "simple",
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"predict" 10
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"predict" : 10
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}
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}
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--------------------------------------------------
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@ -445,4 +445,4 @@ minimization is linear to the size of the window being processed: excessively la
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Finally, minimization fits the model to the last `n` values, where `n = window`. This generally produces
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better forecasts into the future, since the parameters are tuned around the end of the series. It can, however, generate
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poorer fitting moving averages at the beginning of the series.
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======
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======
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