Research Article
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Year 2017, Volume: 10 Issue: 2, 33 - 39, 31.07.2017

Abstract

References

  • Barry, P.J., Beatty, J.C., and Goldman R.N. (1992). Unimodal Properties of B-Splines and Bernstein Basis Functions. Computer-Aided Design, 24(12), 627-636.
  • Bernstein, S.N. (1912). Demonstration du theor`eme de Weierstrass fondee. Communications of the Kharkov Mathematical Society, 13, 1{2.
  • Budakc, G. and Oruc, H. (2012). Bernstein-Schoenberg operator with knots at the q-integers. Mathematical and Computer Modelling, 56(3-4), 56-59.
  • Carnicer, J.M. and Pe~na, J. M. (1994). Totally positive bases for shape preserving curve design and optimality of B-splines. Computer Aided Geometric Design, 11(6), 633-654.
  • Farouki, R.T. (2012). The Bernstein polynomial basis: a centennial retrospective. Computer Aided Geometric Design, 29(6), 379-419.
  • Feller, W. (1971). An Introduction to Probability Theory and Its Applications, Volume 2, 2nd edition. Wiley, New York.
  • Goldman, R.N. (1988). Urn models, Approximations, and Splines. Journal of Approximation Theory, 54, 1-66.
  • Goldman, R.N. (2003). Pyramid Algorithms, A Dynamic Programming Approach to Curves and Surfaces for Geometric Modeling. Elsevier Science, USA.
  • Goodman, T.N.T. and Sharma, A. (1985). A property of Bernstein-Schoenberg spline operators. Proceedings of the Edinburgh Mathematical Society, 28, 333-340.
  • Karlin, S. (1968). Total Positivity, Vol. 1, Stanford University Press, California.
  • Marsden, M. and Schoenberg, I. J. (1966). On Variation Diminishing Spline Approximation Methods. Mathematica, 8(31), 61-82.
  • Marsden, M. J. (1970). An identity for spline functions with applications to variation-diminishing spline approximation. Journal of Approximation Theory, 3, 7-49.
  • Oruç, H. and Phillips, G.M. (2003). q{Bernstein polynomials and Bezier curves. Journal of Computational and Applied Mathematics, 151, 1-12.
  • Phillips, G. M. (2010). A survey of results on the q-Bernstein polynomials. IMA Journal of Numerical Analysis, 30, 277-288.
  • Schoenberg, I.J. (1959). On variation diminishing approximation methods. On Numerical Approximation, MRC Symposium (R.E. Langer ed.). University of Wisconsin Press, Madison, 249-274.
  • Turnbull, B.C. and Ghosh, S.K. (2014). Unimodal density estimation using Bernstein polynomials. Computational Statistics and Data Analysis, 72, 13-29

PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR

Year 2017, Volume: 10 Issue: 2, 33 - 39, 31.07.2017

Abstract

Using Chebyshev's inequality, we provide a probabilistic proof of the uniform convergence for continuous functions on a closed interval by Schoenberg's variation diminishing spline operator. Furthermore, we introduce a unimodal density estimator based on this spline operator and thus generalize that of Bernstein polynomials and beta density. The advantage of this method is the local property. That is, re ning the knots while keeping the degree xed of B-splines yields better estimates. We also give a numerical example to verify our results.

References

  • Barry, P.J., Beatty, J.C., and Goldman R.N. (1992). Unimodal Properties of B-Splines and Bernstein Basis Functions. Computer-Aided Design, 24(12), 627-636.
  • Bernstein, S.N. (1912). Demonstration du theor`eme de Weierstrass fondee. Communications of the Kharkov Mathematical Society, 13, 1{2.
  • Budakc, G. and Oruc, H. (2012). Bernstein-Schoenberg operator with knots at the q-integers. Mathematical and Computer Modelling, 56(3-4), 56-59.
  • Carnicer, J.M. and Pe~na, J. M. (1994). Totally positive bases for shape preserving curve design and optimality of B-splines. Computer Aided Geometric Design, 11(6), 633-654.
  • Farouki, R.T. (2012). The Bernstein polynomial basis: a centennial retrospective. Computer Aided Geometric Design, 29(6), 379-419.
  • Feller, W. (1971). An Introduction to Probability Theory and Its Applications, Volume 2, 2nd edition. Wiley, New York.
  • Goldman, R.N. (1988). Urn models, Approximations, and Splines. Journal of Approximation Theory, 54, 1-66.
  • Goldman, R.N. (2003). Pyramid Algorithms, A Dynamic Programming Approach to Curves and Surfaces for Geometric Modeling. Elsevier Science, USA.
  • Goodman, T.N.T. and Sharma, A. (1985). A property of Bernstein-Schoenberg spline operators. Proceedings of the Edinburgh Mathematical Society, 28, 333-340.
  • Karlin, S. (1968). Total Positivity, Vol. 1, Stanford University Press, California.
  • Marsden, M. and Schoenberg, I. J. (1966). On Variation Diminishing Spline Approximation Methods. Mathematica, 8(31), 61-82.
  • Marsden, M. J. (1970). An identity for spline functions with applications to variation-diminishing spline approximation. Journal of Approximation Theory, 3, 7-49.
  • Oruç, H. and Phillips, G.M. (2003). q{Bernstein polynomials and Bezier curves. Journal of Computational and Applied Mathematics, 151, 1-12.
  • Phillips, G. M. (2010). A survey of results on the q-Bernstein polynomials. IMA Journal of Numerical Analysis, 30, 277-288.
  • Schoenberg, I.J. (1959). On variation diminishing approximation methods. On Numerical Approximation, MRC Symposium (R.E. Langer ed.). University of Wisconsin Press, Madison, 249-274.
  • Turnbull, B.C. and Ghosh, S.K. (2014). Unimodal density estimation using Bernstein polynomials. Computational Statistics and Data Analysis, 72, 13-29
There are 16 citations in total.

Details

Primary Language English
Journal Section Research Article
Authors

Özlem Ege Oruç

M. Sami Erdoğan This is me

Halil Oruç

Publication Date July 31, 2017
Acceptance Date March 10, 2017
Published in Issue Year 2017 Volume: 10 Issue: 2

Cite

APA Ege Oruç, Ö., Erdoğan, M. S., & Oruç, H. (2017). PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR. Istatistik Journal of The Turkish Statistical Association, 10(2), 33-39.
AMA Ege Oruç Ö, Erdoğan MS, Oruç H. PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR. IJTSA. July 2017;10(2):33-39.
Chicago Ege Oruç, Özlem, M. Sami Erdoğan, and Halil Oruç. “PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR”. Istatistik Journal of The Turkish Statistical Association 10, no. 2 (July 2017): 33-39.
EndNote Ege Oruç Ö, Erdoğan MS, Oruç H (July 1, 2017) PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR. Istatistik Journal of The Turkish Statistical Association 10 2 33–39.
IEEE Ö. Ege Oruç, M. S. Erdoğan, and H. Oruç, “PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR”, IJTSA, vol. 10, no. 2, pp. 33–39, 2017.
ISNAD Ege Oruç, Özlem et al. “PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR”. Istatistik Journal of The Turkish Statistical Association 10/2 (July 2017), 33-39.
JAMA Ege Oruç Ö, Erdoğan MS, Oruç H. PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR. IJTSA. 2017;10:33–39.
MLA Ege Oruç, Özlem et al. “PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR”. Istatistik Journal of The Turkish Statistical Association, vol. 10, no. 2, 2017, pp. 33-39.
Vancouver Ege Oruç Ö, Erdoğan MS, Oruç H. PROBABILISTIC APPROACH TO THE SCHOENBERG SPLINE OPERATOR AND UNIMODAL DENSITY ESTIMATOR. IJTSA. 2017;10(2):33-9.