Economics at your fingertips  

Partially observed functional data: The case of systematically missing parts

Dominik Liebl and Stefan Rameseder

Computational Statistics & Data Analysis, 2019, vol. 131, issue C, 104-115

Abstract: New estimators for the mean and the covariance function for partially observed functional data are proposed using a detour via the fundamental theorem of calculus. The new estimators allow for a consistent estimation of the mean and covariance function under specific violations of the missing-completely-at-random assumption. The requirements of the estimation procedure can be tested using a sequential multiple hypothesis test procedure. An extensive simulation study compares the new estimators with the classical estimators from the literature in different missing data scenarios. The proposed methodology is motivated by the practical problem of estimating the mean price curve in the German Control Reserve Market. In this auction market, price curves are only partially observable, and the underlying missing data mechanism depends on systematic trading strategies which clearly violate the missing-completely-at-random assumption. In contrast to the classical estimators, the new estimators lead to useful estimates of the mean and covariance functions. Supplementary materials are provided online.11Supplementary materials: R-package PartiallyFD and R-scripts for reproducing the simulation study and the real data application.

Keywords: Functional data analysis; Missing data; Fundamental theorem of calculus (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only.

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:

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

Page updated 2019-11-24
Handle: RePEc:eee:csdana:v:131:y:2019:i:c:p:104-115