Cited by 2,115Advanced Statistical Methods and ModelsStatistical and numerical algorithmsStatistical Distribution Estimation and Applications

The DOI matches its Crossref record; 17 of the 18 references it cites were found in a registry or an index.

Robust regression using iteratively reweighted least-squares.

Holland, Paul W., Welsch, Roy E.·1977·Communications in Statistics - Theory and Methods

DOI 10.1080/03610927708827533

Open this paper in CoChat — free account

Abstract

The rapid development of the theory of robust estimation (Huber, 1973) has created a need for computational procedures to produce robust estimates. We will review a number of different computational approaches for robust linear regression but focus on one—iteratively reweighted least-squares (IRLS). The weight functions that we discuss are a part of a semi-portable subroutine library called ROSEPACK (RObust Statistical Estimation PACKage) that has been developed by the authors and Virginia Klema at the Computer Research Center of the National Bureau of Economic Research, Inc. in Cambridge, Mass. with the support of the National Science Foundation. This library (Klema, 1976) makes it relatively simple to implement an IRLS regression package.

Integrity signals

Registry

Crossref · 10.1080/03610927708827533

Cites

17 of 17 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Robust estimation of a location parameter
Huber, P. J. (1964) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177703732 · Cited by 7,228
Robust Regression: Asymptotics, Conjectures and Monte Carlo
Huber, P. J. (1973) · The Annals of Statistics · doi:10.1214/aos/1176342503 · Cited by 2,337
The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data
Beaton, A. E., & Tukey, J. W. (1974) · Technometrics · doi:10.1080/00401706.1974.10489171 · Cited by 967
A Robust Method for Multiple Linear Regression
Andrews, D. F. (1974) · Technometrics · doi:10.1080/00401706.1974.10489233 · Cited by 639
An Improved Algorithm for Discrete $l_1 $ Linear Approximation
Barrodale, I., & Roberts, F. D. K. (1973) · SIAM Journal on Numerical Analysis · doi:10.1137/0710069 · Cited by 608
Robust Estimates of Location: Survey and Advances.
HINKLEY, D. V., Andrews, D. F., Bickel, P. J., Hampel, F. R., Huber, P. J., Rogers, W. H., & Tukey, J. W. (1973) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2345006 · Cited by 534
One-Step Huber Estimates in the Linear Model
Bickel, P. J. (1975) · Journal of the American Statistical Association · doi:10.1080/01621459.1975.10479884 · Cited by 338
Robust Estimates of Location: Survey and Advances
Andrews, D. F., & Hampel, F. R. (2015) · Princeton University Press eBooks · doi:10.1515/9781400867011 · Cited by 292
Techniques for nonlinear least squares and robust regression
Dennis, J. E., & Welsch, R. E. (1978) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610917808812083 · Cited by 165
Self-citation
Minimization Techniques for Piecewise Differentiable Functions: The $l_1$ Solution to an Overdetermined Linear System
Bartels, R. H., Conn, A. R., & Sinclair, J. W. (1978) · SIAM Journal on Numerical Analysis · doi:10.1137/0715015 · Cited by 149

Show all 18 references

Research works printed but not linked: 5

Fair R. C., 1974, Ann. Econ. Social Measurement, 3, 667
Gross A. M., 1977, J. Amer. Statist. Assoc.
Hill R. W., 1977, J. Amer. Statist. Assoc.
Klema, V. 1976. Proc. Bicentennial Conf. Math. Program. An iteratively reweighted least squares system. 1976. to appear
Welsch R. E., 1975, 1975 Proc. Amer. Statist. Assoc. Statist. Comp. Section, 36

Sorted by citations

Items 501–600 of 1,000

Ultrahigh‐Resolution Backbone Structure of Perdeuterated Protein GB1 Using Residual Dipolar Couplings from Two Alignment Media
Bouvignies, G., Meier, S., Grzesiek, S., & Blackledge, M. J. (2006) · Angewandte Chemie International Edition · doi:10.1002/anie.200603627 · Cited by 35
Synthesis of the ICESat/ICESat-2 and CryoSat-2 observations to reconstruct time series of lake level
Feng, Y., Yang, L., Zhan, P., Luo, S., Chen, T., Liu, K., & Song, C. (2023) · International Journal of Digital Earth · doi:10.1080/17538947.2023.2166134 · Cited by 35
FILTERING AND DENOISING IN LINEAR REGRESSION ANALYSIS
Hassani, H., Mahmoudvand, R., & Yarmohammadi, M. (2010) · Fluctuation and Noise Letters · doi:10.1142/s0219477510000289 · Cited by 35
The Efficiency of the Biweight as a Robust Estimator of Location
Kafadar, K. (1983) · Journal of Research of the National Bureau of Standards · doi:10.6028/jres.088.006 · Cited by 35
Chapter 11 Estimation for dirty data and flawed models
Krasker, W. S., Kuh, E., & Welsch, R. E. (1983) · Handbook of econometrics · doi:10.1016/s1573-4412(83)01015-6 · Cited by 35
Self-citation
Correlation of spectral solar irradiance with solar activity as measured by VIRGO
Wehrli, C., Schmutz, W. K., & Shapiro, A. I. (2013) · Astronomy and Astrophysics · doi:10.1051/0004-6361/201220864 · Cited by 34
Selective iteratively reweighted quantile regression for baseline correction
Liu, X., Zhang, Z., Sousa, P. F. M., Chen, C., Ouyang, M., Wei, Y., Liang, Y., Chen, Y., & Chaoping, Z. (2014) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-013-7610-x · Cited by 34
Satellite data reveal a common combustion emission pathway for major cities in China
Tang, W., Arellano, A. F., Gaubert, B., Miyazaki, K., & Worden, H. M. (2019) · Atmospheric chemistry and physics · doi:10.5194/acp-19-4269-2019 · Cited by 35
Single-Sensor Source Localization Using Electromagnetic Time Reversal and Deep Transfer Learning: Application to Lightning
Mostajabi, A., Karami, H., Azadifar‬, M., Ghasemi, A., Rubinstein, M., & Rachidi, F. (2019) · Scientific Reports · doi:10.1038/s41598-019-53934-4 · Cited by 34
Picking up Speed: Continuous-Time Lidar-Only Odometry Using Doppler Velocity Measurements
Wu, Y., Yoon, D. J., Burnett, K., Kammel, S., Chen, Y., Vhavle, H., & Barfoot, T. D. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3226068 · Cited by 34
Predictive Scheduling Algorithms for Real-Time Feature Extraction and Spatial Referencing: Application to Retinal Image Sequences
Lin, G., Stewart, C. V., Roysam, B., Fritzsche, K. H., Yang, G., & Tanenbaum, H. L. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2003.820332 · Cited by 34
Enhancement of the classification and reconstruction performance of fuzzy C-means with refinements of prototypes
Reyes-Galaviz, O. F., & Pedrycz, W. (2016) · Fuzzy Sets and Systems · doi:10.1016/j.fss.2016.07.002 · Cited by 34
The role of reserves and production in the market capitalization of oil and gas companies
Ewing, B. T., & Thompson, M. A. (2016) · Energy Policy · doi:10.1016/j.enpol.2016.09.036 · Cited by 34
Inverse depth for accurate photometric and geometric error minimisation in RGB-D dense visual odometry
Gutiérrez-Gómez, D., Mayol-Cuevas, W. W., & Guerrero, J. J. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2015.7138984 · Cited by 33
Linear Accelerometers and Rate Gyros for Rotary Joint Angle Estimation of Heavy-Duty Mobile Manipulators Using Forward Kinematic Modeling
Vihonen, J., Honkakorpi, J., Tuominen, J., Mattila, J., & Visa, A. J. E. (2016) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2016.2544352 · Cited by 33
Identification of Photovoltaic Array Model Parameters by Robust Linear Regression Methods
Piazza, M. C. D., Ragusa, A., & Vitale, G. F. (2017) · Renewable Energy and Power Quality Journal · doi:10.24084/repqj07.268 · Cited by 33
Deindustrialization and Unsustainable Debt in Middle-Income Countries: The Case of Puerto Rico
Caraballo-Cueto, J., & Lara, J. (2017) · Journal of Globalization and Development · doi:10.1515/jgd-2017-0009 · Cited by 33
Post-9/11 Coverage of Terrorism in the New York Times
Mitnik, S. P., Freilich, J. D., & Chermak, S. M. (2018) · Justice Quarterly · doi:10.1080/07418825.2018.1488985 · Cited by 33
A Comparative Analysis of Anthropogenic CO2 Emissions at City Level Using OCO‐2 Observations: A Global Perspective
Fu, P., Xie, Y., Moore, C. E., Myint, S. W., & Bernacchi, C. J. (2019) · Earth s Future · doi:10.1029/2019ef001282 · Cited by 33
Transmitted Home Oximetry and Duration of Home Oxygen in Premature Infants
Rhein, L. M., White, H. O., Simoneau, T., Traeger, N., Lahiri, T., Kremer, T. M., Sheils, C. A., Meyer, K., Rosenkrantz, T. S., Krishnan, S., et al. (2020) · PEDIATRICS · doi:10.1542/peds.2020-0079 · Cited by 33
Topography-based statistical modelling reveals high spatial variability and seasonal emission patches in forest floor methane flux
Vainio, E., Peltola, O., Kasurinen, V., Kieloaho, A., Tuittila, E., & Pihlatie, M. K. (2021) · Biogeosciences · doi:10.5194/bg-18-2003-2021 · Cited by 33
A Robust Loss for Point Cloud Registration
Deng, Z., Yao, Y., Deng, B., & Zhang, J.-Y. (2021) · IEEE International Conference on Computer Vision · doi:10.1109/iccv48922.2021.00608 · Cited by 30
Some convergence properties of iterated reweighted least squares in the location model
Jeffrey, B. B. (1980) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918008812162 · Cited by 33
A configuration-optimisation method for passive-active-combined suspension design
He, H., Li, Y., Clare, L., Jiang, J. Z., Sakka, M. A., Dhaens, M., Burrow, S. G., Neild, S. A., & Conn, A. T. (2023) · International Journal of Mechanical Sciences · doi:10.1016/j.ijmecsci.2023.108560 · Cited by 32
Joint-Space Kinematic Model for Gravity-Referenced Joint Angle Estimation of Heavy-Duty Manipulators
Vihonen, J., Mattila, J., & Visa, A. J. E. (2017) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2017.2749918 · Cited by 32
Scalable Inference of Ordinary Differential Equation Models of Biochemical Processes
Fröhlich, F., Loos, C., & Hasenauer, J. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8882-2_16 · Cited by 32
Source Localization Using Distributed Microphones in Reverberant Environments Based on Deep Learning and Ray Space Transform
Comanducci, L., Borra, F., Bestagini, P., Antonacci, F., Tubaro, S., & Sarti, A. (2020) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2020.3011256 · Cited by 32
Bilevel Methods for Image Reconstruction
Crockett, C., & Fessler, J. A. (2022) · Foundations and Trends® in Signal Processing · doi:10.1561/2000000111 · Cited by 32
EEG effective connectivity during the first year of life mirrors brain synaptogenesis, myelination, and early right hemisphere predominance
Bosch‐Bayard, J., Biscay, R., Fernández, T., Otero, G., Ricardo-Garcell, J., Aubert-Vázquez, E., Evans, A. C., & Harmony, T. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119035 · Cited by 32
Fast simultaneous seismic source separation using Stolt migration and demigration operators
Ibrahim, A., & Sacchi, M. D. (2015) · Geophysics · doi:10.1190/geo2015-0044.1 · Cited by 32
Simultaneous spectrum fitting and baseline correction using sparse representation
Han, Q., Xie, Q., Peng, S., & Guo, B. (2017) · The Analyst · doi:10.1039/c6an02341j · Cited by 32
A robust alternative to the normal distribution
McLeish, D. L. (1982) · Canadian Journal of Statistics · doi:10.2307/3314901 · Cited by 32
Numerical Methods for Robust Regression: Linear Models
Shanno, D. F., & Rocke, D. M. (1986) · SIAM Journal on Scientific and Statistical Computing · doi:10.1137/0907006 · Cited by 32
State anxiety disorganizes finger movements during musical performance
Kotani, S., & Furuya, S. (2018) · Journal of Neurophysiology · doi:10.1152/jn.00813.2017 · Cited by 33
Completely Blind Quality Assessment of User Generated Video Content
Kancharla, P., & Channappayya, S. S. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3130541 · Cited by 31
$L_{1}$-Regularized Reconstruction Model for Edge-Preserving Filtering
Yang, Y., Zheng, H., Zeng, L., Shen, X., & Zhan, Y. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3171686 · Cited by 31
Analysis of hand kinematics reveals inter-individual differences in intertemporal decision dynamics
Calluso, C., Committeri, G., Pezzulo, G., Lepora, N. F., & Tosoni, A. (2015) · Experimental Brain Research · doi:10.1007/s00221-015-4427-1 · Cited by 32
Bahadur Representations for Robust Scale Estimators Based on Regression Residuals
Welsh, A. H. (1986) · The Annals of Statistics · doi:10.1214/aos/1176350064 · Cited by 31
An Automated Hirschberg Test for Infants
Model, D., & Eizenman, M. (2010) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2010.2085000 · Cited by 31
Biological parametric mapping with robust and non-parametric statistics
Yang, X., Beason‐Held, L. L., Resnick, S. M., & Landman, B. A. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.04.046 · Cited by 31
Visual field asymmetries in visual evoked responses
Hagler, D. J. (2014) · Journal of Vision · doi:10.1167/14.14.13 · Cited by 31
Simultaneous localization and calibration for electromagnetic tracking systems
Sadjadi, H., Hashtrudi-Zaad, K., & Gabor Fichtinger, A. (2015) · International Journal of Medical Robotics and Computer Assisted Surgery · doi:10.1002/rcs.1670 · Cited by 31
Kernel-based sparse regression with the correntropy-induced loss
Chen, H., & Wang, Y. (2016) · Applied and Computational Harmonic Analysis · doi:10.1016/j.acha.2016.04.004 · Cited by 31
A visual servoing control law that is robust to image outliers
Comport, A. I., Pressigout, M., Marchand, É., & Chaumette, F. (2004) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2003.1250677 · Cited by 31
Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography
Andrew, M. G., Bijeljic, B., & Blunt, M. J. (2015) · Journal of Visualized Experiments · doi:10.3791/52440 · Cited by 30
Spatiotemporal Differences in the Regional Cortical Plate and Subplate Volume Growth during Fetal Development
Vasung, L., Rollins, C. K., Velasco‐Annis, C., Yun, H. J., Zhang, J., Warfield, S. K., Feldman, H. A., Gholipour, A., & Grant, P. E. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa033 · Cited by 30
Learning an Attention Model for Robust 2-D/3-D Registration Using Point-To-Plane Correspondences
Schaffert, R., Wang, J., Fischer, P., Borsdorf, A., & Maier, A. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.2988410 · Cited by 30
Assessment and development of flow boiling critical heat flux correlations for partially heated rectangular channels in different gravitational environments
Darges, S. J., Devahdhanush, V. S., & Mudawar, I. (2022) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2022.123291 · Cited by 30
Association between vestibulo-ocular reflex suppression, balance, gait, and fall risk in ageing and neurodegenerative disease: protocol of a one-year prospective follow-up study
Srulijes, K., Mack, D. J., Klenk, J., Schwickert, L., Ihlen, E. A. F., Schwenk, M., Lindemann, U., Meyer, M. E., Kc, S., Hobert, M. A., et al. (2015) · BMC Neurology · doi:10.1186/s12883-015-0447-5 · Cited by 30
T2* relaxometry of fetal brain at 1.5 Tesla using a motion tolerant method
Vasylechko, S., Malamateniou, C., Nunes, R. G., Fox, M. J., Allsop, J. M., Rutherford, M., Rueckert, D., & Hajnal, J. V. (2014) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25299 · Cited by 30
Image Processing Issues in Digital Strain Mapping
Clocksin, W. F., da Fonseca, J. Q., Withers, P. J., & Torr, P. H. S. (2002) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.452334 · Cited by 30
Sizing of Molybdenum Nanoparticles Using Time-Resolved Laser-Induced Incandescence
Sipkens, T. A., Joshi, G., Daun, K. J., & Murakami, Y. (2013) · ASME Journal of Heat and Mass Transfer · doi:10.1115/1.4023227 · Cited by 30
Fast, robust, continuous monocular egomotion computation
Jaegle, A., Phillips, S., & Daniilidis, K. (2016) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2016.7487206 · Cited by 30
Joint PET-MR respiratory motion models for clinical PET motion correction
Manber, R., Thielemans, K., Hutton, B. F., Wan, S., McClelland, J. R., Barnes, A., Arridge, S., Sebastien Ourselin, A., & Atkinson, D. (2016) · Physics in Medicine and Biology · doi:10.1088/0031-9155/61/17/6515 · Cited by 30
Modelling Impulse Response Function of Functional Infrared Imaging for General Linear Model Analysis of Autonomic Activity
Perpetuini, D., Cardone, D., Filippini, C., Chiarelli, A. M., & Merla, A. (2019) · Sensors · doi:10.3390/s19040849 · Cited by 30
A robust clustering algorithm based on competitive agglomeration and soft rejection of outliers
Frigui, H., & Krishnapuram, R. J. (1996) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.1996.517126 · Cited by 30
Simultaneous Gut-Brain Electrophysiology Shows Cognition and Satiety Specific Coupling
Balasubramani, P. P., Walke, A., Grennan, G., Purpura, S., Perley, A. S., Ramanathan, D., Coleman, T. P., & Mishra, J. (2022) · Sensors · doi:10.3390/s22239242 · Cited by 31
Sparse Low-Rank Component-Based Representation for Face Recognition With Low-Quality Images
Yang, S., Zhang, L., He, L., & Wen, Y. (2018) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2018.2849883 · Cited by 29
A robust adaptive iterative ensemble smoother scheme for practical history matching applications
Ma, X., & Bi, L. (2019) · Computational Geosciences · doi:10.1007/s10596-018-9786-9 · Cited by 29
Robust parametric modeling of Alzheimer’s disease progression
Ghazi, M. M., Nielsen, M., Pai, A., Marc Modat, A., Cardoso, M. J., Sebastien Ourselin, A., & Sørensen, L. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117460 · Cited by 32
Synchronization Problems in Computer Vision with Closed-Form Solutions
Arrigoni, F., & Fusiello, A. (2019) · International Journal of Computer Vision · doi:10.1007/s11263-019-01240-x · Cited by 29
Input-Adaptive Proxy for Black Carbon as a Virtual Sensor
Fung, P. L., Zaidan, M. A., Sillanpää, S., Kousa, A., Niemi, J. V., Timonen, H., Kuula, J., Saukko, E., Luoma, K., Petäjä, T., et al. (2019) · Sensors · doi:10.3390/s20010182 · Cited by 29
Robust M estimation for 3D correlated vector observations based on modified bifactor weight reduction model
Yang, L., & Shen, Y. (2020) · Journal of Geodesy · doi:10.1007/s00190-020-01351-1 · Cited by 29
Review of Outlier Detection and Identifying Using Robust Regression Model
Begashaw, G. B., & Yohannes, Y. B. (2020) · International Journal of Systems Science and Applied Mathematics · doi:10.11648/j.ijssam.20200501.12 · Cited by 29
Learning under (1 + ϵ)-moment conditions
Feng, Y., & Wu, Q. (2020) · Applied and Computational Harmonic Analysis · doi:10.1016/j.acha.2020.05.009 · Cited by 29
Equivalence of Partial-Least-Squares SEM and the Methods of Factor-Score Regression
Yuan, K., & Deng, L. (2021) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2021.1894940 · Cited by 29
Fast and Robust Non-Rigid Registration Using Accelerated Majorization-Minimization
Yao, Y., Deng, B., Xu, W., & Zhang, J. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3247603 · Cited by 29
Compressibility of Sands of Various Geologic Origins at Pre-crushing Stress Levels
Zheng, J., Hryciw, R. D., & Ventola, A. (2017) · Geotechnical and Geological Engineering · doi:10.1007/s10706-017-0225-9 · Cited by 29
Detecting and Localizing End-to-End Performance Degradation for Cellular Data Services Based on TCP Loss Ratio and Round Trip Time
Ahmed, F., Erman, J., Ge, Z., Liu, A. X., Wang, J., & Yan, H. (2017) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2017.2761758 · Cited by 29
Robust Hemodynamic Response Function Estimation From fNIRS Signals
Seghouane, A., & Ferrari, D. (2019) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2019.2899289 · Cited by 29
Dissecting beta-state changes during timed movement preparation in Parkinson’s disease
Heideman, S. G., Quinn, A. J., Woolrich, M. W., van Ede, F., & Nobre, A. C. (2019) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2019.101731 · Cited by 29
Positioning in 5G Networks: Emerging Techniques, Use Cases, and Challenges
Abuyaghi, M., Si-Mohammed, S., Shaker, G. S. A., & Rosenberg, C. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3487822 · Cited by 28
Climate Change Impacts in the Design of Drainage Systems: Case Study of Portugal
Pereira, M., Fernandes, L. F. S., Macário, E. B., GASPAR, S., & Pinto, J. G. (2014) · Journal of Irrigation and Drainage Engineering · doi:10.1061/(asce)ir.1943-4774.0000788 · Cited by 28
Structure and Deformation History of the Rapidly Growing Tainan Anticline at the Deformation Front of the Taiwan Mountain Belt
Béon, M. L., Marc, O., Suppe, J., Huang, M., Huang, S., & Chen, W. (2019) · Tectonics · doi:10.1029/2019tc005510 · Cited by 28
Robust penalized extreme learning machine regression with applications in wind speed forecasting
Yang, Y., Zhou, H., Gao, Y., Wu, J., Wang, Y., & Fu, L. (2021) · Neural Computing and Applications · doi:10.1007/s00521-021-06370-3 · Cited by 28
Pixel-Perfect Structure-From-Motion With Featuremetric Refinement
Sarlin, P.-E., Lindenberger, P., Larsson, V., & Pollefeys, M. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3237269 · Cited by 34
An Improved Method to Moho Depth Recovery From Gravity Disturbance and Its Application in the South China Sea
Li, J., Xu, C., & Chen, H. (2022) · Journal of Geophysical Research Solid Earth · doi:10.1029/2022jb024536 · Cited by 28
Efficient Terrain-Aided Visual Horizon Based Attitude Estimation and Localization
Dumble, S. J., & Gibbens, P. W. (2014) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-014-0043-8 · Cited by 28
What determines the spatial pattern in summer upwelling trends on the U.S. West Coast?
Seo, H., Brink, K. H., Dorman, C. E., Koracin, D. R., & Edwards, C. A. (2012) · Journal of Geophysical Research Atmospheres · doi:10.1029/2012jc008016 · Cited by 32
Pressure image assimilation for atmospheric motion estimation
Corpetti, T., Héas, P., Mémin, É., & Papadakis, N. (2008) · Tellus A Dynamic Meteorology and Oceanography · doi:10.1111/j.1600-0870.2008.00370.x · Cited by 28
On the use of robust regression in econometrics
Baldauf, M., & Silva, J. S. (2011) · Economics Letters · doi:10.1016/j.econlet.2011.09.031 · Cited by 28
Robust Regression using Probability Plots for Estimating the Weibull Shape Parameter
Zhang, L. ‐., Xie, M., & Tang, L. C. (2006) · Quality and Reliability Engineering International · doi:10.1002/qre.778 · Cited by 28
Photometric Stereo Under Non-uniform Light Intensities and Exposures
Cho, D., Matsushita, Y., Tai, Y., & Kweon, I.-S. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46475-6_11 · Cited by 28
High Accuracy Quantum Chemical and Thermochemical Network Data for the Heats of Formation of Fluorinated and Chlorinated Methanes and Ethanes
Ganyecz, Á., Kállay, M., & Csontos, J. (2018) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.8b00614 · Cited by 28
Altered modulation of gamma oscillation frequency by speed of visual motion in children with autism spectrum disorders
Stroganova, T. A., Butorina, A. V., Sysoeva, O., Prokofyev, A. O., Nikolaeva, A. Y., Tsetlin, M. M., & Orekhova, E. V. (2015) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-015-9121-x · Cited by 29
M-estimator for the 3D symmetric Helmert coordinate transformation
Chang, G., Xu, T., & Wang, Q. (2017) · Journal of Geodesy · doi:10.1007/s00190-017-1043-9 · Cited by 27
SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations
Zhang, S., & Lin, G. (2020) · Journal of Computational Physics · doi:10.1016/j.jcp.2020.109962 · Cited by 27
Evaluating the roles of electrolyte components on the passivation of silicon anodes
Malkowski, T. F., Yang, Z., Sacci, R. L., Trask, S. E., Rodrigues, M. F., Bloom, I., & Veith, G. M. (2022) · Journal of Power Sources · doi:10.1016/j.jpowsour.2022.231021 · Cited by 27
Subcooled flow boiling heat transfer in a partially-heated rectangular channel at different orientations in Earth gravity
Devahdhanush, V. S., & Mudawar, I. (2022) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2022.123200 · Cited by 27
Tensor-based keypoint detection and switching regression model for relative radiometric normalization of bitemporal multispectral images
Moghimi, A., Çelik, T., & Mohammadzadeh, A. (2022) · International Journal of Remote Sensing · doi:10.1080/01431161.2022.2102951 · Cited by 27
Retinal Vascular Changes in Alzheimer's Dementia and Mild Cognitive Impairment: A Pilot Study Using Ultra-Widefield Imaging
Pead, E., Thompson, A. C., Grewal, D. S., McGrory, S., Robbins, C. B., Ma, J. P., Johnson, K. G., Liu, A., Hamid, C., Trucco, E., et al. (2023) · Translational Vision Science & Technology · doi:10.1167/tvst.12.1.13 · Cited by 27
A Comparison of Robust and Nonparametric Estimators under the Simple Linear Regression Model.
Nevitt, J., & Tam, H. P. (1997) · General Linear Model Journal · Cited by 27
On robust Kalman filtering with forgetting factor for sequential speech analysis
Yang, T., Lee, J., Lee, K. Y., & Sung, K.-M. (1997) · Signal Processing · doi:10.1016/s0165-1684(97)00150-3 · Cited by 27
Robust inversion using biweight norm and its application to seismic inversion
Ji, J. (2012) · Exploration Geophysics · doi:10.1071/eg12014 · Cited by 27
Robust statistical methods for impulse noise suppressing of spread spectrum induced polarization data, with application to a mine site, Gansu province, China
Liu, W., Chen, R., Cai, H., & Luo, W. (2016) · Journal of Applied Geophysics · doi:10.1016/j.jappgeo.2016.04.020 · Cited by 27
Predictive Classification of Water Consumption Time Series Using Non-homogeneous Markov Models
Leyli-Abadi, M., Samé, A., Oukhellou, L., Cheifetz, N., Mandel, P., Féliers, C., & Chesneau, O. (2017) · IEEE International Conference on Data Science and Advanced Analytics (DSAA) · doi:10.1109/dsaa.2017.32 · Cited by 27
GNSS Multipath Error Modeling and Mitigation by Using Sparsity-Promoting Regularization
Chen, C., Chang, G., Zheng, N., & Xu, T. (2019) · IEEE Access · doi:10.1109/access.2019.2899622 · Cited by 27
Algorithms for accurate 3D registration of neuronal images acquired by confocal scanning laser microscopy
Al-Kofahi, O., Can, A. B., Lasek, S., Szarowski, D. H., Turner, J. N., & Roysam, B. (2003) · Journal of Microscopy · doi:10.1046/j.1365-2818.2003.01196.x · Cited by 27
Robust Analysis of Covariance
Birch, J. B., & Myers, R. H. (1982) · Biometrics · doi:10.2307/2530050 · Cited by 27
Iteratively Reweighted Least Squares
Jorgensen, M. A. (2006) · Encyclopedia of Environmetrics · doi:10.1002/9780470057339.vai022 · Cited by 27

Authors: Holland, P. W., & Welsch, R. E.
Affiliations: Educational Testing Service (US)
National Bureau of Economic Research (US)
ORCID: Holland, Paul W.
Welsch, Roy E.
Venue: Communications in Statistics - Theory and Methods
Publisher: Informa UK Limited
Published: 1977-01
Volume: 6
Issue: 9
Pages: 813-827
ISSN: 0361-0926 (ISSN-L)
1532-415X
DOI: 10.1080/03610927708827533
OpenAlex: W2050551672
Cited by: 2,115
References: 18
Citations by year: 2026: 97 · 2025: 112 · 2024: 121 · 2023: 110 · 2022: 123 · 2021: 123 · 2020: 128 · 2019: 103 · 2018: 105 · 2017: 108 · 2016: 104 · 2015: 101 · 2014: 101 · 2013: 61 · 2012: 48
FWCI: 5.33
Type: journal article
Language: en
Open access: closed
Locations: Communication in Statistics- Theory and Methods (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
Keywords: robust regression, iteratively reweighted least squares, robust estimation, weight functions, robust linear regression

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Robust regression using iteratively reweighted least-squares.

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks