Non‐parametric small area models using shape‐constrained penalized B‐splines

Julian Wagner, Ralf Münnich, Joachim Hill, Johannes Stoffels and Thomas Udelhoven

Journal of the Royal Statistical Society Series A, 2017, vol. 180, issue 4, 1089-1109

Abstract: For the estimation of spruce timber reserves in individual forest districts of the German federal state Rhineland‐Palatinate, small area methods are applied. A model using stock values of the state forest inventory and a canopy height model derived by airborne laser scanning is used to provide adequate estimates. Since the interaction between the variables is non‐linear and must fulfil further constraints, a new spline‐based small area estimation method is proposed, formulated as a quadratic programming problem. This method enables providing realistic estimates via including specialized constraints which are especially important in practice as well as more stable estimates. The applicability of the new method and the related mean‐squared‐error estimators is shown in a simulation study. Further, spruce timber reserves in Rhineland‐Palatinate are estimated by using the new approach compared with already existing methods.

Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://doi.org/10.1111/rssa.12295

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:180:y:2017:i:4:p:1089-1109

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-985X

Access Statistics for this article

Journal of the Royal Statistical Society Series A is currently edited by A. Chevalier and L. Sharples

More articles in Journal of the Royal Statistical Society Series A from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().