Article
MSC:
60F05,
60F99,
62E20,
62G08,
62J02,
62J05,
62J20 | MR 2411126 | Zbl 1197.62075 | DOI: 10.1007/s10492-008-0006-0
Full entry |
PDF
(0.6 MB)
Feedback
PDF
(0.6 MB)
Feedback
Keywords:
regression quantiles; basic solution; misspecified model
regression quantiles; basic solution; misspecified model
Summary:
We consider the asymptotic distribution of covariate values in the quantile regression basic solution under weak assumptions. A diagnostic procedure for assessing homogeneity of the conditional densities is also proposed.
References:
[1] Angrist, J., Chernozhukov, V., Fernández-Val, I.: Quantile regression under misspecification with an application to the U.S. wage structure. Econometrica 74 (2006), 539-563. DOI 10.1111/j.1468-0262.2006.00671.x | MR 2207400
[2] Jun., G. Bassett, Koenker, R.: Asymptotic theory of least absolute error regression. J. Am. Stat. Assoc. 73 (1978), 618-622. DOI 10.1080/01621459.1978.10480065 | MR 0514166 | Zbl 0391.62046
[3] Chernozhukov, V., Fernández-Val, I.: Subsampling inference on quantile regression processes. Sankhya 67 (2005), 253-276. MR 2208889 | Zbl 1192.62128
[4] Dantzig, G. B.: Linear Programming and Extensions. Princeton University Press Princeton (1951). MR 1658673
[5] Fiacco, A. V., McCormick, G. P.: Nonlinear Programming: Sequential Unconstrained Minimization Techniques. Wiley New York (1968). MR 0243831 | Zbl 0193.18805
[6] Hastings, W. K.: Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57 (1970), 97-109. DOI 10.1093/biomet/57.1.97 | Zbl 0219.65008
[7] Karmarker, N.: A new polynomial time algorithm for linear programming. Combinatorica 4 (1984), 373-395. DOI 10.1007/BF02579150 | MR 0779900
[8] Khmaladze, E. V.: An innovative approach to goodness-of-fit tests in $\Bbb R^m$. Ann. Stat. 16 (1988), 1503-1516. DOI 10.1214/aos/1176351051 | MR 0964936
[9] Knight, K., Goh, C.: Asymptotics of quantile regression solutions with application. Manuscript in preparation.
[10] Koenker, R.: Quantile Regression. Cambridge University Press Cambridge (2005). MR 2268657 | Zbl 1111.62037
[11] Koenker, R., Bassett, G. W.: Regression quantiles. Econometrica 46 (1978), 33-50. DOI 10.2307/1913643 | MR 0474644 | Zbl 0373.62038
[12] Koenker, R., d'Orey, V.: Computing regression quantiles. Appl. Stat. 36 (1987), 383-393. DOI 10.2307/2347802
[13] Koenker, R., Park, B. J.: An interior point algorithm for nonlinear quantile regression. J. Econom. 71 (1996), 265-283. DOI 10.1016/0304-4076(96)84507-6 | MR 1381085 | Zbl 0855.62030
[14] Koenker, R., Xiao, Z.: Inference on the quantile regression process. Econometrica 70 (2002), 1583-1612. DOI 10.1111/1468-0262.00342 | MR 1929979 | Zbl 1152.62339
[15] Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., Teller, E.: Equations of state calculations by fast computing machines. J. Chem. Phys. 21 (1953), 1087-1092. DOI 10.1063/1.1699114
[16] Mukhin, A. B.: Local limit theorems for distributions of sums of independent random vectors. Theory Probab. Appl. 29 (1985), 369-375. MR 0749924 | Zbl 0557.60019
[17] Mukhin, A.: Local limit theorems for lattice random variables. Theory Probab. Appl. 36 (1991), 698-713. DOI 10.1137/1136086 | MR 1147168 | Zbl 0776.60027
Search
Partner of
