6533b858fe1ef96bd12b62da
RESEARCH PRODUCT
Estimating regression models with unknown break-points.
Vito M. R. Muggeosubject
Statistics and ProbabilityProper linear modelMultivariate adaptive regression splinesModels StatisticalEpidemiologyLinear modelDustMarginal modelSurvival AnalysisLinear predictor functionStatisticsLinear regressionChronic DiseaseApplied mathematicsHeart TransplantationHumansRegression AnalysisSegmented regressionBronchitisRegression diagnosticMathematicsdescription
This paper deals with fitting piecewise terms in regression models where one or more break-points are true parameters of the model. For estimation, a simple linearization technique is called for, taking advantage of the linear formulation of the problem. As a result, the method is suitable for any regression model with linear predictor and so current software can be used; threshold modelling as function of explanatory variables is also allowed. Differences between the other procedures available are shown and relative merits discussed. Simulations and two examples are presented to illustrate the method.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2003-09-16 | Statistics in medicine |