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Bootstrap estimatio...
Bootstrap estimation of the variance of the error term in monotonic regression models
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- Sysoev, Oleg (författare)
- Linköpings universitet,Tekniska högskolan,Statistik
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- Grimvall, Anders (författare)
- Linköpings universitet,Tekniska högskolan,Statistik
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- Burdakov, Oleg, 1953- (författare)
- Linköpings universitet,Tekniska högskolan,Optimeringslära
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(creator_code:org_t)
- Taylor & Francis Group, 2013
- 2013
- Engelska.
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Ingår i: Journal of Statistical Computation and Simulation. - : Taylor & Francis Group. - 0094-9655 .- 1563-5163. ; 83:4, s. 625-638
- Relaterad länk:
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https://urn.kb.se/re...
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visa fler...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- The variance of the error term in ordinary regression models and linear smoothers is usually estimated by adjusting the average squared residual for the trace of the smoothing matrix (the degrees of freedom of the predicted response). However, other types of variance estimators are needed when using monotonic regression (MR) models, which are particularly suitable for estimating response functions with pronounced thresholds. Here, we propose a simple bootstrap estimator to compensate for the over-fitting that occurs when MR models are estimated from empirical data. Furthermore, we show that, in the case of one or two predictors, the performance of this estimator can be enhanced by introducing adjustment factors that take into account the slope of the response function and characteristics of the distribution of the explanatory variables. Extensive simulations show that our estimators perform satisfactorily for a great variety of monotonic functions and error distributions.
Ämnesord
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- uncertainty estimation; bootstrap; monotonic regression; pool-adjacent-violators algorithm
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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