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KARŞILAŞTIRMALI OLARAK FONKSİYONEL ANA BİLEŞENLER ANALİZİ VE GSYİH VERİLERİNİN İNCELENMESİ

Year 2008, Volume: 8 Issue: 2, 915 - 928, 01.10.2008

İstem Köymen Keser

Abstract

Bu çalışmada öncelikle Ana Bileşenler ve Fonksiyonel Ana Bileşenler Analizi karşılaştırmalı olarak ele alınmış ve ekonomik gelişmenin bir göstergesi olan Gayri Safi Yurt İçi Hasıla (GSYİH) verileri Fonksiyonel Ana Bileşenler Analizi ile incelenerek verileri fonksiyonel açıdan ele almanın avantajları sunulmuştur. Fonksiyonel Ana Bileşenler Analizi ile 1987-2001 yılları arasında ülkemizdeki 7 bölgenin GSYİH verilerinin değişkenlik yapısı %99 gibi çok yüksek bir varyans açıklama yüzdesine sahip birinci ana bileşen fonksiyonuyla ortaya konulmuştur. Bu ana bileşen fonksiyonun yardımıyla GSYİH açısından bölgeler arasındaki değişkenliğin 1996 yılından sonra bir artışa geçtiği, ancak 2000 yılının ortalarından sonra da tekrar azalmaya başladığı tespit edilmiştir

Keywords

Fonksiyonel Veri Analizi Fonksiyonel Ana Bileşenler Analizi

References

  • ANDERSON T.W. (2003). “An Introduction to Multivariate Statistical
  • Analysis”,Wiley-Interscience, USA BARRA V. (2004). “Analysis of Gene Expression Data Using Functional
  • Principal Components”, Computer Methods and Programs in Biomedicine, (1):1-9. BENKO M. (2004). “Functional Principal Components analysis, Implementation and Applications”. A Master Thesis, Humboldt University Center of Applied
  • Statistics and Economics, Berlin. BENKO M., HARDLE W., and KNEİP A.(2006). “Common Functional Principal
  • Components” SFB 649, DiscussionPaper http://ideas.repec.org/p/hum/wpaper/sfb649dp2006-010.html, (10.11.2006)
  • CASTRO P. E, LAWTON W. H., and SYLVESTRE E. A. (1986). “Principal
  • Modes Of Variation for Processes with Continuous Sample Curves” ,Technometrics, 28(4 ):329-337. HALL P. and NASAB H. M. (2006). “On Properties Of Functional Principal
  • Components Analysis”, Journal of the Royal Statistical Society: Series B, (1):109-126. JAMES G. M., HASTİE T.J., and SUGAR C.A. (2000), “Principal Components
  • Models For Sparse Functional Data”, Biometrica, 87(3):587-602. JOLIFFE I.T. (2002). “Principal Component Analysis”,Springer – Verlag, New York.
  • LEE H.J. (2004). “Functional Data Analysis: Classification and Regression”.
  • Doctor of Philosophy, Texas A&M University. LOBER E.M., and VİLLA C. (2004). “Functional Principal Component Analysis of the Yield Curve”, http://www.u-cergy.fr/AFFI_2004/IMG/pdf/MATZNER.pdf, (05.05.2005).
  • LOBER E.M., and VİLLA C. (2004). “Functional Principal Component Analysis of the Yield Curve”, http://www.u-cergy.fr/AFFI_2004/IMG/pdf/MATZNER.pdf, (05.05.2005).
  • LYCHE, T. and MORKEN, K., (2002). “Spline Methods Draft”, http://www.ifi.uio.no/in329/nchap1.pdf ,( 10.07.2005).
  • MARDİA K.V., KENT J.T., and BİBBY J.M. (1989). “Multivariate Analysis”,
  • Academic Press, London. RAMSAY J.O., & SİLVERMAN B.W. (2005). “Functional Data Analysis” Second
  • Edition, Springer , USA. RAMSAY J.O., (2000). “Functional Principal Component Analysis”, , ftp://ego.psych.mcgill.ca, (11.04.2005).
  • RAMSAY J.O., and SİLVERMAN B.W. (1997). “Functional Data Analysis”,
  • Springer – Verlag, New York. RAMSAY, J. O., and DALZELL C. (1991). “Some Tools For Functional Data
  • Analysis”, Journal of the Royal Statistical Society: Series B.,53 (3):539-572. RAMSAYJ.O.,(2003).,http://www.psych.mcgill.ca/faculty/ramsay/ramsay.html, (11.04.2005).
  • TÜİK (2007), http://www.tuik.gov.tr, (14.08. 2007 ).
  • YAMANİSHİ Y., & TANAKA Y. (2005). “Sensitivity Analysis in Functional
  • Principal Component Analysis” Computational Statistics, 20(2):313-329.

FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA

Year 2008, Volume: 8 Issue: 2, 915 - 928, 01.10.2008

İstem Köymen Keser

Abstract

In this study, Principal Components and Functional Principal Components Analyses discussed comparatively. Gross Domestic Product (GDP) data is analyzed by Functional Principal Component Analysis and the advantages of dealing data in a functional way is presented. GDP data (between 1987 and 2001) for seven regions of Turkey is studied by Functional Principal Component Analysis, it is found that %99 of the variation structure can be explained by the first principal component function. It is also revealed that the variation between regions began to increase after the year 1996. However, it began to decrease rapidly after year 2000

Keywords

Functional Data Analysis Functional Principal Component Analysis

References

  • ANDERSON T.W. (2003). “An Introduction to Multivariate Statistical
  • Analysis”,Wiley-Interscience, USA BARRA V. (2004). “Analysis of Gene Expression Data Using Functional
  • Principal Components”, Computer Methods and Programs in Biomedicine, (1):1-9. BENKO M. (2004). “Functional Principal Components analysis, Implementation and Applications”. A Master Thesis, Humboldt University Center of Applied
  • Statistics and Economics, Berlin. BENKO M., HARDLE W., and KNEİP A.(2006). “Common Functional Principal
  • Components” SFB 649, DiscussionPaper http://ideas.repec.org/p/hum/wpaper/sfb649dp2006-010.html, (10.11.2006)
  • CASTRO P. E, LAWTON W. H., and SYLVESTRE E. A. (1986). “Principal
  • Modes Of Variation for Processes with Continuous Sample Curves” ,Technometrics, 28(4 ):329-337. HALL P. and NASAB H. M. (2006). “On Properties Of Functional Principal
  • Components Analysis”, Journal of the Royal Statistical Society: Series B, (1):109-126. JAMES G. M., HASTİE T.J., and SUGAR C.A. (2000), “Principal Components
  • Models For Sparse Functional Data”, Biometrica, 87(3):587-602. JOLIFFE I.T. (2002). “Principal Component Analysis”,Springer – Verlag, New York.
  • LEE H.J. (2004). “Functional Data Analysis: Classification and Regression”.
  • Doctor of Philosophy, Texas A&M University. LOBER E.M., and VİLLA C. (2004). “Functional Principal Component Analysis of the Yield Curve”, http://www.u-cergy.fr/AFFI_2004/IMG/pdf/MATZNER.pdf, (05.05.2005).
  • LOBER E.M., and VİLLA C. (2004). “Functional Principal Component Analysis of the Yield Curve”, http://www.u-cergy.fr/AFFI_2004/IMG/pdf/MATZNER.pdf, (05.05.2005).
  • LYCHE, T. and MORKEN, K., (2002). “Spline Methods Draft”, http://www.ifi.uio.no/in329/nchap1.pdf ,( 10.07.2005).
  • MARDİA K.V., KENT J.T., and BİBBY J.M. (1989). “Multivariate Analysis”,
  • Academic Press, London. RAMSAY J.O., & SİLVERMAN B.W. (2005). “Functional Data Analysis” Second
  • Edition, Springer , USA. RAMSAY J.O., (2000). “Functional Principal Component Analysis”, , ftp://ego.psych.mcgill.ca, (11.04.2005).
  • RAMSAY J.O., and SİLVERMAN B.W. (1997). “Functional Data Analysis”,
  • Springer – Verlag, New York. RAMSAY, J. O., and DALZELL C. (1991). “Some Tools For Functional Data
  • Analysis”, Journal of the Royal Statistical Society: Series B.,53 (3):539-572. RAMSAYJ.O.,(2003).,http://www.psych.mcgill.ca/faculty/ramsay/ramsay.html, (11.04.2005).
  • TÜİK (2007), http://www.tuik.gov.tr, (14.08. 2007 ).
  • YAMANİSHİ Y., & TANAKA Y. (2005). “Sensitivity Analysis in Functional
  • Principal Component Analysis” Computational Statistics, 20(2):313-329.
There are 22 citations in total.

Details

Other ID JA66RH25HV
Journal Section Research Article
Authors

İstem Köymen Keser This is me

Publication Date October 1, 2008
Published in Issue Year 2008 Volume: 8 Issue: 2

Cite

APA Keser, İ. K. (2008). FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA. Ege Academic Review, 8(2), 915-928.
AMA Keser İK. FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA. ear. October 2008;8(2):915-928.
Chicago Keser, İstem Köymen. “FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA”. Ege Academic Review 8, no. 2 (October 2008): 915-28.
EndNote Keser İK (October 1, 2008) FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA. Ege Academic Review 8 2 915–928.
IEEE İ. K. Keser, “FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA”, ear, vol. 8, no. 2, pp. 915–928, 2008.
ISNAD Keser, İstem Köymen. “FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA”. Ege Academic Review 8/2 (October 2008), 915-928.
JAMA Keser İK. FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA. ear. 2008;8:915–928.
MLA Keser, İstem Köymen. “FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA”. Ege Academic Review, vol. 8, no. 2, 2008, pp. 915-28.
Vancouver Keser İK. FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS: INVESTIGATION OF GDP DATA. ear. 2008;8(2):915-28.