Journal of the American Statistical Association, 2015-03, Vol.110 (509), p.233-245
2015
Details
- Autor(en) / Beteiligte
- Titel
- Model-Robust Designs for Quantile Regression
- Ist Teil von
- Journal of the American Statistical Association, 2015-03, Vol.110 (509), p.233-245
- Ort / Verlag
- Alexandria: Taylor & Francis
- Erscheinungsjahr
- 2015
- Link zum Volltext
- Quelle
- Alma/SFX Local Collection
- Beschreibungen/Notizen
- We give methods for the construction of designs for regression models, when the purpose of the investigation is the estimation of the conditional quantile function, and the estimation method is quantile regression. The designs are robust against misspecified response functions, and against unanticipated heteroscedasticity. The methods are illustrated by example, and in a case study in which they are applied to growth charts.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1537-274X, 0162-1459eISSN: 1537-274XDOI: 10.1080/01621459.2014.969427Titel-ID: cdi_crossref_primary_10_1080_01621459_2014_969427
- Format
- –
- Schlagworte
- Asymptotic mean squared error, B-splines, Case studies, Charts, Compound design, Estimating techniques, Estimation, Exchange algorithm, Genetic algorithm, Growth charts, Growth theory, Heteroscedasticity, heteroskedasticity, Mathematical functions, Mathematical models, Minimax bias, Minimax mean squared error, Nonlinear models, Regression analysis, Regression quantiles, Statistics, Theory and Methods, Uniformity