Revista de Matemática: Teoría y Aplicaciones ISSN Impreso: 1409-2433 ISSN electrónico: 2215-3373

OAI: https://revistas.ucr.ac.cr/index.php/matematica/oai
Frequency polygons for random fields (density estimation for random fields)
PDF (Español (España))

Keywords

random field
frequency polygons
bandwidth
campos aleatorios
polígono de frecuencia
ancho de banda

How to Cite

Carbon, M. (2007). Frequency polygons for random fields (density estimation for random fields). Revista De Matemática: Teoría Y Aplicaciones, 14(2), 105–122. https://doi.org/10.15517/rmta.v14i2.39304

Abstract

The purpose of this paper is to investigate the frequency polygon as a density estimator for stationary random fields indexed by multidimensional lattice points space. Optimal bin widths which asymptotically minimize integrated errors (IMSE) are derived. Under weak conditions, frequency polygons achieve the same rate of convergence to zero of the IMSE as kernel estimators. They can also attain the optimal uniform rate of convergence under general conditions. Frequency polygons thus appear to be very good density estimators with respect to both criteria of IMSE and uniform convergence.

https://doi.org/10.15517/rmta.v14i2.39304
PDF (Español (España))

References

Bolthausen, E. (1982) “On the central limit theorem for stationary random fields”, Ann. Probab. 10: 1047–1050.

Bradley, R.C. (1986) “Basic properties of strong mixing conditions. In : Dependence in Probability and Statistics, vol 11, Birkh¨auser: 165–192.

Carbon, M., Tran, L.T. and Wu, B. (1997) “Kernel density estimation for random fields (Density estimation for random fields)”, Statistics and Probability Letters 36: 115–125.

Carbon, M., Hallin, M. and Tran, L.T. (1996) “Kernel density estimation for random fields: The L1 theory”, Journal of Non Parametric Statistics 6: 157–170.

Carbon, M. (2006) “Polygones des fréquences pour des champs aléatoires”, Comptes Rendus de l’Académie des Sciences de Paris, A paraître.

Davydov, Yu A. (1970) “The invariant principle for stationary processes”, Theor. Probab. Appl. 14: 487–498.

Gorodetskii, V.V. (1977) “On the strong mixing property for linear sequences”, Theory Probability Appl. 22: 411–413.

Guyon, X.; Richardson, S. (1984) “Vitesse de convergence du théorème de la limite centrale pour des champs faiblement dépendants”, Z. Wahrsch. Verw. Gebiete 66: 297–314.

Guyon, X. (1987) “Estimation d’un champ par pseudo-vraisemblance conditionnelle: Etude ´ asymptotique et application au cas Markovien”, Proc. 6th Franco-Belgian Meeting of Statisticians.

Hall, P.; Hannan, E.J. (1988) “On stochastic complexity and nonparametric density estimation”, Biometrika 75: 705–714.

Ibragimov, I. A.; Linnik, Yu. V. (1971) Independent and Stationary Sequences of Random Variables. Wolters-Noordhoff, Groningen.

Masry, E.; Gy¨orfi (1987) “Strong consistency and rates for recursive density estimators for stationary mixing processes”, J. Multivariate Anal. 22: 79–93.

Nahapetian, B. S. (1980) “The central limit theorem for random fields with mixing conditions”, in: R. L. Dobrushin & Ya G. Sinai (Eds.) Adv. in Probability 6, Multicomponent Systems: 531–548.

Nahapetian, B. S. (1987) “An approach to proving limit theorems for dependent random variables”, Theory Prob. Appl. 32: 535–539.

Neaderhouser, C. C. (1980) “Convergence of block spins defined on random fields”, J. Statist. Phys. 22: 673–684.

Politis, D. N.; Romano, J. P. (1993). “Nonparametric resampling for homogeneous strong mixing random fields”, J. Multivariate Anal. 47: 301–328.

Rio, E. (1995) “The functional law of the iterated logarithm for stationary strongly mixing sequences”, Ann. Prob. 23: 1188–1203.

Robinson, P.M. (1983) “Nonparametric estimators for time series”, J. Time Series Anal. 4: 185–207.

Rosenblatt, M. (1985) Stationary Sequences and Random Fields. Birkhäuser, Boston.

Roussas, G.G. (1969) “Nonparametric estimation of the transition distribution of a Markov process”, Ann. Inst. Statist. Math. 21: 73–87.

Roussas, G.G. (1988) “Nonparametric estimation in mixing sequences of random variables”, Jour. Statist. Plann. Inference 18: 135–149.

Scott, D.W. (1985) “Frequency polygons, theory and applications”, J. Amer. Stat. Assoc. 80: 348–354.

Stone, C.J. (1983) “Optimal unifom rate of convergence for non parametric estimators of a density function and its derivative”, in: M.H. Revzi, J.S. Rustagi & D. Siegmund (Eds.) Recent Advances in Statistics: Papers in Honor of H. Chernoff: 393–406.

Takahata, H. (1983) “On the rates in the central limit theorem for weakly dependent random fields”, Z. Wahrsch. Verw. Gebiete 62: 477–480.

Tran, L.T. (1990) “Kernel density estimation on random fields”, J. Multivariate Anal. 34: 37–53.

Tran, L.T.; Yakowitz, S. (1993) “Nearest neighbor estimators for random fields”, J. Multivariate Anal. 44: 23–46.

Comments

Downloads

Download data is not yet available.