Abstract
This chapter introduces functional data analysis, a relatively new technique for data analysis in Business Analytics. The distinct feature of this technique is that it deals with smooth functions or processes, which generate the discretized data sample that we observe. The functional approach allows us to flexibly model system dynamics, to analyze observations with measurement errors, and to fit data with sparse observations. We illustrate the application of functional data analysis in the capital structure of California hospitals. We also point out the functional data analysis application in business research and future research directions.
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References
Ramsay JO, Dalzell C (1991) Some tools for functional data analysis. J R Stat Soc Series B (Methodological):539–572
Ramsay JO, Silverman BW (2005) Functional data analysis. Springer, New York
Sood A, James GM, Tellis GJ (2009) Functional regression: a new model for predicting market penetration of new products. Mark Sci 28(1):36–51
Jank W, Shmueli G (2006) Functional data analysis in electronic commerce research. Stat Sci 21(2):155–166
Ramsay JO, Ramsey JB (2002) Functional data analysis of the dynamics of the monthly index of nondurable goods production. J Econ 107(1):327–344
Abraham C, Cornillon P-A, Matzner‐Løber E, Molinari N (2003) Unsupervised curve clustering using B‐splines. Scand J Stat 30(3):581–595
Gastón M, León T, Mallor F (2008) Functional data analysis for non homogeneous poisson processes. In: Simulation conference WSC 2008, Winter. IEEE, Piscataway, NJ, pp 337–343
Bapna R, Jank W, Shmueli G (2008) Price formation and its dynamics in online auctions. Decis Support Syst 44(3):641–656
Wang S, Jank W, Shmueli G (2008) Explaining and forecasting online auction prices and their dynamics using functional data analysis. J Bus Econ Stat 26(2)
Foutz NZ, Jank W (2010) Research note-prerelease demand forecasting for motion pictures using functional shape analysis of virtual stock markets. Mark Sci 29(3):568–579
Graves S, Hooker G, Ramsay J (2009) Functional data analysis with R and MATLAB. Springer, New York
De Boor C, De Boor C, De Boor C, De Boor C (1978) A practical guide to splines, vol 27. Springer, New York
Schumaker LL (1981) Spline functions: basic theory, vol 1981. Wiley, New York
Craven P, Wahba G (1978) Smoothing noisy data with spline functions. Numer Math 31(4):377–403
Duda RO, Hart PE (1973) Pattern classification and scene analysis, vol 3. Wiley, New York
National Quality Measures C Gastrointestinal (GI) hemorrhage: mortality rate. Agency for Healthcare Research and Quality (AHRQ). http://www.qualitymeasures.ahrq.gov/content.aspx?id=38495. Accessed 11 June 2014
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Mai, F., Wu, C. (2015). Functional Data Analysis with an Application in the Capital Structure of California Hospitals. In: García Márquez, F., Lev, B. (eds) Advanced Business Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-11415-6_11
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DOI: https://doi.org/10.1007/978-3-319-11415-6_11
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