Strengths and weaknesses of S-curves

Theodore Modis

No r5zk7, OSF Preprints from Center for Open Science

Abstract: For the last 22 years I have been fitting logistic S-curves to data points of historical time series at an average rate of about 2–3 per day. This amounts to something between 15,000 and 20,000 fits. Combined with the 40,000 fits of the Monte Carlo study we did with Alain Debecker to quantify the uncertainties in logistic fits [1], probably qualifies me for an entry in the Guinness Book of Records as the man who carried out the greatest number of logistic fits. It hasn't all been fun and games. There have also been blood and tears and not only from human errors. There have been what I came to recognize as “misbehaviors” of reality. I have seen cases where an excellent fit and ensuing forecast were invalidated by later data. But well-established logistic growth reflects the action of a natural law. A disproved forecast is tantamount to violating this law. A law that becomes violated is not much of a law. What is going on? There is something here that needs to be sorted out.

Date: 2007-07-05
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Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:r5zk7

DOI: 10.31219/osf.io/r5zk7

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