Quantiles conditionnels

Sandrine Poiraud-Casanova; Christine Thomas-Agnan

Journal de la société française de statistique (1998)

  • Volume: 139, Issue: 4, page 31-44
  • ISSN: 1962-5197

How to cite

top

Poiraud-Casanova, Sandrine, and Thomas-Agnan, Christine. "Quantiles conditionnels." Journal de la société française de statistique 139.4 (1998): 31-44. <http://eudml.org/doc/199555>.

@article{Poiraud1998,
author = {Poiraud-Casanova, Sandrine, Thomas-Agnan, Christine},
journal = {Journal de la société française de statistique},
keywords = {Monotonicity; Regression quantile; Min-Max formula},
language = {fre},
number = {4},
pages = {31-44},
publisher = {Société de statistique de Paris},
title = {Quantiles conditionnels},
url = {http://eudml.org/doc/199555},
volume = {139},
year = {1998},
}

TY - JOUR
AU - Poiraud-Casanova, Sandrine
AU - Thomas-Agnan, Christine
TI - Quantiles conditionnels
JO - Journal de la société française de statistique
PY - 1998
PB - Société de statistique de Paris
VL - 139
IS - 4
SP - 31
EP - 44
LA - fre
KW - Monotonicity; Regression quantile; Min-Max formula
UR - http://eudml.org/doc/199555
ER -

References

top
  1. ANTOCH J., JANSSEN P. (1989). Non parametric regression M-quantiles. Statistics & Probability Letters. 8 pp. 355-362. Zbl0682.62022MR1028994
  2. BERLINET A., CADRE B., GANNOUN A. (1998). Estimation non paramétrique de la médiane conditionnelle spatiale. Preprint. 
  3. BERLINET A., GANNOU A., MATZNER-LOBER E. (1997). Asymptotic normality of the non parametric estimator of conditional median under mixing conditions. Preprint. 
  4. BERLINET A., GANNOUN A., MATZNER-LOBER E. (1998). Propriétés asymptotiques d'estimateurs convergents des quantiles conditionnels. C. R. Arcad. Sci. Paris, t. Série 1, pp. 611-614. Zbl0918.62044
  5. BHATTACHARYA P.K., GANGOPADHYAY A.K. (1990). Kernel and nearest-neighbor estimation of a conditional quantile. Ann. Math. Statist. 18 (3) pp. 1400-1415. Zbl0706.62040MR1062716
  6. BOENTE G., FRAIMAN R. (1995). Asymptotic distribution of smoothers based on local means and local medians under dependance. Journal of Multivariate Analysis. 54 pp. 77-90. Zbl0898.62043MR1345528
  7. CHAUDURI P. (1991). Nonparametric estimates of regression quantiles and their local Bahadur representation. Ann. Math. Statist. 19 (2) pp. 760-777. Zbl0728.62042MR1105843
  8. CHENG C., PARZEN E. (1997). Unified estimators of smooth quantile and quantile density functions. Journal of Statistical and Planning Inference. 59 pp. 291-307. Zbl0900.62209MR1450503
  9. COLE T.J., GREEN P.J. (1992). Smoothing reference centile curves : the LMS method and penalized likelihood. Statistics in Medecine. 11 pp. 1305-1319. 
  10. CSORGO M., HORVATH L. (1993). Weighted approximation in probability and statistics. Wiley, New-York. Zbl0770.60038MR1215046
  11. CSORGO M., REVEZC P. (1984). Two approaches to constructing simultaneous confidence bounds for quantiles. Prob. and Math. Statist. 4 pp. 221-236. Zbl0591.62039MR792787
  12. DAVIS C.E., HARRELL F.E. (1982). A new distribution-free quantile estimator. Biometrika. 69 (3) pp. 635-640. Zbl0493.62038MR695209
  13. DUCHARME G.R., GANNOUN A., GUERTIN M.C., JEQUIER J.C. (1995). Reference values obtained by kernel-based estimation of quantile regression. Biometrics. 51 pp. 1105- 1116. Zbl0875.62153
  14. FALK M. (1984). Relative deficiency of Kernel type estimators of quantiles. Ann. Math. Statist. 12 (1) pp. 261-268. Zbl0533.62040MR733512
  15. FAN J., HU T. C., TRUONG Y.K. (1994). Robust nonparametric function estimation. Scand. J. Statist. 21 pp. 433-446. Zbl0810.62038MR1310087
  16. GANNOUN A. (1991). Prédiction non paramétrique : médianogramme et méthode du noyau en estimation de la médiane conditionnelle. Statistique et Analyse des données. 16 (1) pp. 23-42. 
  17. GOLDSTEIN H., PAN H. (1992). Percentile smoothing using piecewise polynomials with covariates. Biometrics. 48 pp. 1057- 1068. MR1212857
  18. HART J.D. (1991). Comment to "Choosing a kernel regression estimator". Statistical Sciences. 6 pp. 425-427. MR1146907
  19. HE X., SHI P. (1994). Convergence rate of B-spline estimators of non parametric conditional quantile functions. Nonparametric Statistics. 3 pp. 299-308. Zbl05143418MR1291551
  20. HOGG R.V. (1975). Estimates of pourcentile regression lines using salary data. Journal of the American Statistical Association. 70 pp. 56-59. 
  21. KAIGH W.D., CHENG C. (1991). Subsampling quantile estimators and uniformity criteria. Comm. Statist A. 20 pp. 539-560. Zbl0747.62032MR1130945
  22. KAIGH W.D., LACHENBRUCH P.A. (1982). A generalized quantile estimator. Comm. Statist A. 11 pp. 2217-2238. Zbl0499.62034MR677013
  23. KOENKER R., BASSETT G. (1978). Regression quantiles. Econometrica. 46 (1). Zbl0373.62038MR474644
  24. KOENKER R., BASSETT G. (1982). An empirical quantile function for linear models with i.i.d. errors. Journal of the American Statistical Association. 77 pp. 407-415. Zbl0493.62047MR664682
  25. KOENKER R., NG P., PORTNOY S. (1994). Quantile smoothing splines. Biometrika.81 (4) pp. 673-680. Zbl0810.62040MR1326417
  26. LEJEUNE M.G., SARDA P. (1988). Quantile regression : a nonparametric approach. Computational Statistics & Data Analysis. 6 pp. 229-239. Zbl0726.62057MR943904
  27. MARTINS ROSA A.C., DELECROIX M. (1992). Ergodic processes prediction via estimation of the conditional distribution function. Pub I.S.U.P. vol XXXIX fasc 2, 95, pp. 35-56. Zbl0834.62089
  28. MUKERJEE H. (1993). An improved monotone conditional quantile estimator. Ann. Math. Statist. 21 (2) pp. 924-942. Zbl0789.62025MR1232526
  29. PADGETT W.J., LIO Y.L. (1993). A smooth nonparametric quantile estimator for IFR distributions. Nonparametric Statistics. 2 pp. 195-202. Zbl05143381MR1256382
  30. PARZEN E.. (1979). Nonparametric statistical data modeling (with comments). Journal of the American Statistical Association. 74 pp. 105-131. Zbl0407.62001MR529528
  31. POIRAUD-CASANOVA S., THOMAS-AGNAN C. (1998). Monotone nonparametric regression quantiles. Cahier technique n° 97.09.452. GREMAQ, 21 Allées de Brienne 31000 Toulouse, France. Zbl1048.62037
  32. SAMANTA M. (1989). Nonparametric estimation of conditional quantiles. Statistic and probability letters. 7 (5) pp. 407-412. Zbl0678.62049MR1001144
  33. SCHUMAKER L.L. (1981). Spline functions. Wiley. Zbl0449.41004MR606200
  34. SHEATHER S.J., MARRON J.S. (1990). Kernel quantile estimators. Journal of the American Statistical Association. 85 pp. 410-416. Zbl0705.62042MR1141741
  35. SONESSON S.E., FOURON J.C., DOBLIK S.P., TAWILE C., LESSARD M., SKOLL A., GUERTIN M.C., DUCHARME G.R. (1993). Reference values for Doppler velocimetric indices from the fetal and placental ends of the umbilical artery during normal pregnancy. Journal of Clinical Ultrasound. 21 pp. 317-324. 
  36. STONE C.J. (1977). Consistent nonparametric regression. Ann. Math. Statist. 5(4) pp.595-645. Zbl0366.62051MR443204
  37. STUTE W. (1986). Conditional empirical processes. Ann. Math. Statist. 14(2) pp. 638-647. Zbl0594.62038MR840519
  38. TRUONG Y.K. (1989). Asymptotic properties of kernel estimators based on local medians. Ann. Math. Statist. 17(2) pp. 606-617. Zbl0675.62031MR994253
  39. TSYBAKOV A.B. (1986). Robust reconstruction of functions by the local-approximation method. Problems of Information Transmission. 22 pp. 133-146. Zbl0622.62047MR855002
  40. YAMATO H. (1973). Uniform convergence of an estimation of a distribution function. Bull. Math. Statist. 15 pp. 69-70. Zbl0277.62032MR329113
  41. YANG S.S. (1985). A smooth nonparametric estimator of a quantile function. Journal of the American Statistical Association. 80 (392), Theory and Methods, pp. 1004-1011. Zbl0593.62037MR819607
  42. YU K., JONES M.C. (1998). Local linear quantile regression. Journal of the American Statistical Association. 93 (441) pp. 228-237. Zbl0906.62038MR1614628
  43. ZELTERMAN D. (1990). Smooth nonparametric estimation of the quantile function. Journal of Statistical and Plannig Inference. 26 pp. 339-352. Zbl0734.62039MR1086105

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.