1 |
Alhamzawi, R. (2015). Model selection in quantile regression models, Journal of Applied Statistics, 42, 445-458.
DOI
|
2 |
Atkinson, A. C. (1994). Fast very robust methods for the detection of multiple outliers, Journal of the American Statistical Association, 89, 1329-1339.
DOI
|
3 |
Atkinson, A. C. (2009). Econometric applications of the forward search in regression: Robustness, diagnostics, and graphics, Econometric Reviews, 28, 21-39.
|
4 |
Atkinson, A. C. and Cheng, T. C. (2000). On robust linear regression with incomplete data, Computational Statistics & Data Analysis, 33, 361-380.
DOI
|
5 |
Atkinson, A. C. and Riani, M. (2007a). Exploratory tools for clustering multivariate data, Computational Statistics & Data Analysis, 52, 272-285.
DOI
|
6 |
Atkinson, A. C. and Riani, M. (2007b). Building regression models with the forward search, Journal of Computing and Information Technology, 15, 287-294.
DOI
|
7 |
Bastero, R. F. and Barrios, E. B. (2011). Robust estimation of a spatiotemporal model with structural change, Communications in Statistics-Simulation and Computation, 40, 448-468.
DOI
|
8 |
Beran, R. (1982). Robust estimation in models for independent non-identically distributed data, The Annals of Statistics, 10, 415-428.
DOI
|
9 |
Bertaccini, B. and Varriale, R. (2007). Robust analysis of variance: An approach based on the forward search, Computational Statistics & Data Analysis, 51, 5172-5183.
DOI
|
10 |
Campano, W. Q. and Barrios, E. B. (2011). Robust estimation of a time series model with structural change, Journal of Statistical Computation and Simulation, 81, 909-927.
DOI
|
11 |
Cantoni, E. and Ronchetti, E. (2001). Robust inference for generalized linear models, Journal of the American Statistical Association, 96, 1022-1030.
DOI
|
12 |
Cao, F., Ye, H. and Wang, D. (2015). A probabilistic learning algorithm for robust modeling using neural networks with random weights, information sciences, 313, 62-78.
DOI
|
13 |
Carroll, R. J. and Ruppert, D. (1982). Robust estimation in heteroscedastic linear models, The Annals of Statistics, 10, 429-441.
DOI
|
14 |
Chang, L., Hu, B., Chang, G. and Li, A. (2013). Robust derivative-free Kalman filter based on Huber's M-estimation, Journal of Process Control, 23, 1555-1561.
DOI
|
15 |
Cizek, P. (2008). Robust and efficient adaptive estimation of binary-choice regression models, Journal of the American Statistical Association, 103, 687-696.
DOI
|
16 |
Cizek, P. (2012). Semiparametric robust estimation of truncated and censored regression models, Journal of Econometrics, 168, 347-366.
DOI
|
17 |
Cressie, N. and Hawkins, D. M. (1980). Robust estimation of the variogram: I, Mathematical Geology, 12, 115-125.
DOI
|
18 |
Dang, V. A., Kim, M. and Shin, Y. (2015). In search of robust methods for dynamic panel data models in empirical corporate finance, Journal of Banking & Finance, 53, 84-98.
DOI
|
19 |
de Luna, X. and Genton, M. G. (2001). Robust simulation-based estimation of ARMA models, Journal of Computational and Graphical Statistics, 10, 370-387.
DOI
|
20 |
Dogan, O. and Taspinar, S. (2014). Spatial autoregressive models with unknown heteroscedasticity: A comparison of Bayesian and robust GMM approach, Regional Science and Urban Economics, 45, 1-21.
DOI
|
21 |
Field, C. A., Pang, Z. and Welsh, A. H. (2010). Bootstrapping robust estimates for clustered data, Journal of the American Statistical Association, 105, 1606-1616.
DOI
|
22 |
Furno, M. (2004). ARCH tests and quantile regressions, Journal of Statistical Computation and Simulation, 74, 277-292.
DOI
|
23 |
Gaglianone, W. P., Lima, L. R., Linton, O. and Smith, D. R. (2011). Evaluating value-at-risk models via quantile regression, Journal of Business & Economic Statistics, 29, 150-160.
DOI
|
24 |
Hampel, F. R. (1971). A general qualitative definition of robustness, The Annals of Mathematical Statistics, 42, 1887-1896.
DOI
|
25 |
Hampel, F. R. (1973). Robust estimation: A condensed partial survey, Zeitschrift fur Wahrscheinlichkeitstheorie und Verwandte Gebiete, 27, 87-104.
DOI
|
26 |
Hampel, F. R. (1974). The influence curve and its role in robust estimation, Journal of the American Statistical Association, 69, 383-393.
DOI
|
27 |
Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J. and Stahel, W. A. (1986). Robust Statistics: The Approach Based on Influence Functions, John Wiley & Sons, New York.
|
28 |
Hardle, W. (1984). Robust regression function estimation, Journal of Multivariate Analysis, 14, 169-180.
DOI
|
29 |
Hastie, T. J. and Tibshirani, R. J. (1990). Generalized Additive Models, Chapman and Hall, London.
|
30 |
He, X. and Zhu, L. X. (2003). A lack-of-fit test for quantile regression, Journal of the American Statistical Association, 98, 1013-1022.
DOI
|
31 |
He, X., Fung, W. Z. and Zhu, Z. (2005). Robust estimation in generalized partial linear models for clustered data, Journal of the American Statistical Association, 100, 1176-1184.
DOI
|
32 |
Hettmansperger, T. P. and McKean, J. W. (1988). Robust Nonparametric Statistical Methods, Arnold, London.
|
33 |
Hettmansperger, T. P., McKean, J. W., and Sheather, S. J. (2000). Robust nonparametric methods, Journal of the American Statistical Association, 95, 1308-1312.
DOI
|
34 |
Hoshino, T. (2014). Quantile regression estimation of partially linear additive models, Journal of Nonparametric Statistics, 26, 509-536.
DOI
|
35 |
Huang, A. Y. H. (2012). Volatility forecasting by quantile regression, Applied Economics, 44, 423-433.
DOI
|
36 |
Huber, P. J. (1964). Robust estimation of a location parameter, The Annals of Mathematical Statistics, 35, 73-101.
DOI
|
37 |
Huber, P. J. (1972). The 1972 wald lecture robust statistics: A review, The Annals of Mathematical Statistics, 43, 1041-1067.
DOI
|
38 |
Huber, P. J. (1973). Robust regression: Asymptotics, conjectures and Monte Carlo, The Annals of Statistics, 1, 799-821.
DOI
|
39 |
Huber, P. J. (2002). John W. Tukey's contributions to robust statistics, The Annals of Statistics, 30, 1640-1648.
DOI
|
40 |
Huber, P. J. and Ronchetti, E. M. (2009). Robust Statistics, 2nd ed., John Wiley and Sons, New York.
|
41 |
Hubert, M. and Rousseeuw, P. J. (1997). Robust regression with both continuous and binary regressors, Journal of Statistical Planning and Inference, 57, 153-163.
DOI
|
42 |
Hung, K. W. and Siu, W. C. (2015). Learning-based image interpolation via robust k-NN searching for coherent AR parameters estimation, Journal of Visual Communication Image Representation, 31, 305-311.
DOI
|
43 |
Kim, M. O. and Yang, Y. (2011). Semiparametric approach to a random effects quantile regression, Journal of the American Statistical Association, 106, 1405-1417.
DOI
|
44 |
Karunamuni, R. J., Tang, Q. and Zhao, B. (2015). Robust and efficient estimation of effective dose, Computational Statistics & Data Analysis, 90, 47-60.
DOI
|
45 |
Kelly, G. E. and Lindsey, J. K. (2002). Robust estimation of the median lethal dose, Journal of Biopharmaceutical Statistics, 12, 137-147.
DOI
|
46 |
Kitromilidou, S. and Fokianos, K. (2015). Robust estimation methods for a class of log-linear count time series models, Journal of Statistical Computation and Simulation, DOI: 10.1080/00949655.2015.1035271.
DOI
|
47 |
Li, Y. and Zhu, J. (2008). L1-norm quantile regression, Journal of Computational and Graphical Statistics, 17, 163-185.
DOI
|
48 |
Lv, Z., Zhu, H. and Yu, K. (2014). Robust variable selection for nonlinear models with diverging number of parameters, Statistics & Probability Letters, 91, 90-97.
DOI
|
49 |
Mann, H. B. and Wald, A. (1942). On the choice of the number of class intervals in the application of the chi square test, The Annals of Mathematical Statistics, 13, 306-317.
DOI
|
50 |
Maronna, R. A. and Zamar, R. H. (2002). Robust estimates of location and dispersion for high dimensional datasets, Technometrics, 44, 307-317.
DOI
|
51 |
Mavridis, D. and Moustaki, I. (2009). The forward search algorithm for detecting response patterns in factor analysis for binary data, Journal of Computational and Graphical Statistics, 18, 1016-1034.
DOI
|
52 |
Moscone, F. and Tosetti, E. (2015). Robust estimation under error cross section dependence, Economics Letters, 133, 100-104.
DOI
|
53 |
Rieder, H. (1996). Robust Statistics, Data Analysis, and Computer Intensive Methods, Springer-Verlag, New York.
|
54 |
Nassiri, V. and Loris, I. (2013). A generalized quantile regression model, Journal of Applied Statistics, 40, 1090-1105.
DOI
|
55 |
Perez, B., Molina, I. and Pena, D. (2014). Outlier detection and robust estimation in linear regression models with fixed group effects, Journal of Statistical Computation and Simulation, 84, 2652-2669.
DOI
|
56 |
Riani, M. (2004). Extensions of the forward search to time series, Studies in Nonlinear Dynamics & Econometrics, 8, Article 2.
|
57 |
Sacks, J. and Ylvisaker, D. (1972). A note of Huber's robust estimation of a location parameter, The Annals of Mathematical Statistics, 43, 1068-1075.
DOI
|
58 |
Santos, K. C. P. and Barrios, E. B. (2015). Improving predictive accuracy of logistic regression model using ranked set samples, Communications in Statistics-Simulation and Computation, DOI: 10.1080/03610918.2014.955113.
DOI
|
59 |
Shahriari, H. and Ahmadi, O. (2015). Robust estimation of the mean vector for high-dimensional data set using robust clustering, Journal of Applied Statistics, 42, 1183-1205.
DOI
|
60 |
Tukey, J. W. (1962). The future of data analysis, The Annals of Mathematical Statistics, 33, 1-67.
DOI
|
61 |
Ursu, E. and Pereau, J. C. (2014). Robust modelling of periodic vector autoregressive time series, Journal of Statistical Planning and Inference, 155, 93-106.
DOI
|
62 |
Vretos, N., Tefas, A. and Pitas, I. (2013). Using robust dispersion estimation in support vector machines, Pattern Recognition, 46, 3441-3451.
DOI
|
63 |
Xiao, Z. (2012). Robust inference in nonstationary time series models, Journal of Econometrics, 169, 211-223.
DOI
|
64 |
Wang, Y., Fan, Y., Bhatt, P. and Davatzikos, C. (2010). High-dimensional pattern regression using machine learning: From medical images to continuous clinical variables, Neuroimage, 50, 1519-1535.
DOI
|
65 |
Wei, Y. and Carroll, R. J. (2009). Quantile regression with measurement error, Journal of American Statistical Association, 104, 1129-1143.
DOI
|
66 |
Wong, R. K.W., Yao, F. and Lee, T. C. M. (2014). Robust estimation for generalized additive models, Journal of Computational and Graphical Statistics, 23, 270-289.
DOI
|
67 |
Zhao, J. and Wang, J. (2009). Robust testing procedures in heteroscedastic linear models, Communications in Statistics-Simulation and Computation, 38, 244-256.
DOI
|