Skip to main content
SpringerLink
Log in

Regression Estimation

  • Chapter
  • First Online:
Asymmetric Kernel Smoothing

Part of the book series: SpringerBriefs in Statistics ((JSSRES))

  • 712 Accesses

Abstract

As mentioned in Chap. 1, research in asymmetric kernels appears to begin with regression estimation. This chapter investigates nonparametric regression estimation smoothed by asymmetric kernels.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Ahn, D.H., and B. Gao. 1999. A parametric nonlinear model of term structure dynamics. Review of Financial Studies 12: 721–762.

    Article  Google Scholar 

  • Arapis, M., and J. Gao. 2006. Empirical comparisons in short-term interest rate models using nonparametric methods. Journal of Financial Econometrics 4: 310–345.

    Article  Google Scholar 

  • Brownlees, C. T., F. Cipollini, and G. M. Gallo. 2012. Multiplicative error models. In Handbook of  Volatility Models and Their Applications, ed. L. Bauwens, C. Hafner and S. Laurent, 223–247. Hoboken, NJ: John Wiley & Sons.

    Google Scholar 

  • Burman, P., E. Chow, and D. Nolan. 1994. A cross-validatory method for dependent data. Biometrika 81: 351–358.

    Article  MathSciNet  Google Scholar 

  • Chapman, D.A., and N.D. Pearson. 2000. Is the short rate drift actually nonlinear? Journal of Finance 55: 355–388.

    Article  Google Scholar 

  • Chen, S.X. 2000. Beta kernel smoothers for regression curves. Statistica Sinica 10: 73–91.

    Google Scholar 

  • Chen, S.X. 2002. Local linear smoothers using asymmetric kernels. Annals of the Institute of Statistical Mathematics 54: 312–323.

    Article  MathSciNet  Google Scholar 

  • Cox, J.C., J.E. Ingersoll Jr., and S.A. Ross. 1985. A theory of the term structure of interest rates. Econometrica 53: 385–408.

    Article  MathSciNet  Google Scholar 

  • Engle, R.F. 2002. New frontiers for ARCH models. Journal of Applied Econometrics 17: 425–446.

    Article  Google Scholar 

  • Fan, J. 1993. Local linear regression smoothers and their minimax efficiencies. Annals of Statistics 21: 196–216.

    Article  MathSciNet  Google Scholar 

  • Fan, J., and I. Gijbels. 1992. Variable bandwidth and local linear regression smoothers. Annals of Statistics 20: 2008–2036.

    Article  MathSciNet  Google Scholar 

  • Fan, J., and C. Zhang. 2003. A reexamination of diffusion estimators with applications to financial model validation. Journal of the American Statistical Association 98: 118–134.

    Article  MathSciNet  Google Scholar 

  • Gasser, T., and H.-G. Müller. 1979. Kernel estimation of regression functions. In Smoothing Techniques for Curve Estimation: Proceedings of a Workshop Held in Heidelberg, April 2–4, 1979, ed. T. Gasser and M. Rosenblatt, 23–68. Berlin: Springer-Verlag.

    Google Scholar 

  • Gospodinov, N., and M. Hirukawa. 2012. Nonparametric estimation of scalar diffusion models of interest rates using asymmetric kernels. Journal of Empirical Finance 19: 595–609.

    Article  Google Scholar 

  • Gouriéroux, C., and J. Jasiak. 2006. Autoregressive gamma processes. Journal of Forecasting 25: 129–152.

    Google Scholar 

  • Györfi, L., W. Härdle, P. Sarda, and P. Vieu. 1989. Nonparametric Curve Estimation from Time Series, Lecture Notes in Statistics. Berlin: Springer-Verlag.

    Google Scholar 

  • Härdle, W., and P. Vieu. 1992. Kernel regression smoothing of time series. Journal of Time Series Analysis 13: 209–232.

    Google Scholar 

  • Masry, E., and J. Fan. 1997. Local polynomial estimation of regression functions for mixing processes. Scandinavian Journal of Statistics 24: 165–179.

    Article  MathSciNet  Google Scholar 

  • Nadaraya, É.A. 1964. On estimating regression. Theory of Probability and Its Applications 9: 141–142.

    Google Scholar 

  • Seifert, B., and T. Gasser. 1996. Finite-sample variance of local polynomials: analysis and solutions. Journal of the American Statistical Association 91: 267–275.

    Article  MathSciNet  Google Scholar 

  • Shi, J., and W. Song. 2016. Asymptotic results in gamma kernel regression. Communications in Statistics – Theory and Methods 45: 3489–3509.

    Article  MathSciNet  Google Scholar 

  • Stanton, R. 1997. A nonparametric model of term structure dynamics and the market price of interest rate risk. Journal of Finance 52: 1973–2002.

    Article  Google Scholar 

  • Watson, G.S. 1964. Smooth regression analysis. Sankhyā: The Indian Journal of Statistics, Series A 26: 359–372.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Economics, Ryukoku University, Kyoto, Japan

    Masayuki Hirukawa

Authors
  1. Masayuki Hirukawa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Masayuki Hirukawa .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 The Author(s)

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Hirukawa, M. (2018). Regression Estimation. In: Asymmetric Kernel Smoothing. SpringerBriefs in Statistics(). Springer, Singapore. https://doi.org/10.1007/978-981-10-5466-2_4

Download citation

Publish with us

Policies and ethics

Search

Navigation