A new maximum likelihood algorithm for piecewise regression

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Abstract

This paper presents a piecewise regression method for continuous models containing max or min operators, or both. This method does not require knowledge of the zone in which a shift in regimes occurs. Moreover, it allows the application of analytical derivatives to maximize the likelihood function, which greatly simplifies the estimation of the model. The method proposed exhibits fast convergence and can be used for an arbitrary number of regimes and variables.

Original languageEnglish
Pages (from-to)980-987
Number of pages8
JournalJournal of the American Statistical Association
Volume76
Issue number376
DOIs
StatePublished - Dec 1981

Funding

FundersFunder number
Israel Institute of Business Research
Tel Aviv University

    Keywords

    • Linear and nonlinear regression
    • Piecewise regression
    • Regression

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