Functional Data Analysis of Payment Systems

In this paper for a credit cards payment system as robust predictor of transactions number and transactions intensity is proposed by means of functional autoregressive model. Intraday economic time series are treated as random continuous functions projected onto low dimensional subspace. Both B-spl...

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Main Authors:	A. Laukaitis, A. Račkauskas
Format:	Article
Language:	English
Published:	Vilnius University Press 2002-12-01
Series:	Nonlinear Analysis
Subjects:	high frequency data functional AR model functional data analysis B-splines Fourier bases credit cards payment system
Online Access:	http://www.zurnalai.vu.lt/nonlinear-analysis/article/view/15194

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spelling	doaj-db6816c01f31472290d78ccbda03b8a22020-11-25T02:12:16ZengVilnius University PressNonlinear Analysis1392-51132335-89632002-12-0172Functional Data Analysis of Payment SystemsA. Laukaitis0A. Račkauskas1Institute of Mathematics and Informatics, LithuaniaVilnius University; Institute of Mathematics and Informatics, Lithuania In this paper for a credit cards payment system as robust predictor of transactions number and transactions intensity is proposed by means of functional autoregressive model. Intraday economic time series are treated as random continuous functions projected onto low dimensional subspace. Both B-splines and Fourier bases are considered for data smoothing. http://www.zurnalai.vu.lt/nonlinear-analysis/article/view/15194high frequency datafunctional AR modelfunctional data analysisB-splinesFourier basescredit cards payment system
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	A. Laukaitis A. Račkauskas
spellingShingle	A. Laukaitis A. Račkauskas Functional Data Analysis of Payment Systems Nonlinear Analysis high frequency data functional AR model functional data analysis B-splines Fourier bases credit cards payment system
author_facet	A. Laukaitis A. Račkauskas
author_sort	A. Laukaitis
title	Functional Data Analysis of Payment Systems
title_short	Functional Data Analysis of Payment Systems
title_full	Functional Data Analysis of Payment Systems
title_fullStr	Functional Data Analysis of Payment Systems
title_full_unstemmed	Functional Data Analysis of Payment Systems
title_sort	functional data analysis of payment systems
publisher	Vilnius University Press
series	Nonlinear Analysis
issn	1392-5113 2335-8963
publishDate	2002-12-01
description	In this paper for a credit cards payment system as robust predictor of transactions number and transactions intensity is proposed by means of functional autoregressive model. Intraday economic time series are treated as random continuous functions projected onto low dimensional subspace. Both B-splines and Fourier bases are considered for data smoothing.
topic	high frequency data functional AR model functional data analysis B-splines Fourier bases credit cards payment system
url	http://www.zurnalai.vu.lt/nonlinear-analysis/article/view/15194
work_keys_str_mv	AT alaukaitis functionaldataanalysisofpaymentsystems AT arackauskas functionaldataanalysisofpaymentsystems
_version_	1724910416865263616

Functional Data Analysis of Payment Systems

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