Anne Ruiz-Gazen

Personal Details

First Name:	Anne
Middle Name:
Last Name:	Ruiz-Gazen
Suffix:
RePEc Short-ID:	pru145
	https://www.tse-fr.eu/people/anne-ruiz-gazen

Affiliation

Groupe de Recherche en Économie Mathématique et Quantitative (GREMAQ)
Toulouse School of Economics (TSE)

Toulouse, France
http://www-gremaq.univ-tlse1.fr/
RePEc:edi:getlsfr (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Nguyen, T.H.A & Laurent, Thibault & Thomas-Agnan, Christine & Ruiz-Gazen, Anne, 2018. "Analyzing the impacts of socio-economic factors on French departmental elections with CODA methods," TSE Working Papers 18-961, Toulouse School of Economics (TSE).
   • T. H. A. Nguyen & T. Laurent & C. Thomas-Agnan & A. Ruiz-Gazen, 2022. "Analyzing the impacts of socio-economic factors on French departmental elections with CoDa methods," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(5), pages 1235-1251, April.
   • Thi-Huong-An Nguyen & Thibault Laurent & Christine Thomas-Agnan & Anne Ruiz-Gazen, 2022. "Analyzing the impacts of socio-economic factors on French departmental elections with CoDa methods," Post-Print hal-03721994, HAL.

   Cited by:

   1. Jacob Fiksel & Scott Zeger & Abhirup Datta, 2022. "A transformation‐free linear regression for compositional outcomes and predictors," Biometrics, The International Biometric Society, vol. 78(3), pages 974-987, September.
   2. Thi Huong An Nguyen & Anne Ruiz-Gazen & Christine Thomas-Agnan & Thibault Laurent, 2019. "Multivariate Student versus Multivariate Gaussian Regression Models with Application to Finance," JRFM, MDPI, vol. 12(1), pages 1-21, February.
   3. Thomas-Agnan, Christine & Morais, Joanna, 2019. "Covariates impacts in compositional models and simplicial derivatives," TSE Working Papers 19-1057, Toulouse School of Economics (TSE).
   4. Joanna Morais & Christine Thomas-Agnan, 2021. "Impact of covariates in compositional models and simplicial derivatives," Post-Print hal-03180682, HAL.
   5. Bačo, Tomáš & Baumöhl, Eduard, 2021. "Socioeconomic factors and shifts in ideological orientation among political parties: Parliamentary elections in Slovakia from 1998 to 2020," EconStor Preprints 246584, ZBW - Leibniz Information Centre for Economics.

2. Juillard, Hélène & Chauvet, Guillaume & Ruiz-Gazen, Anne, 2016. "Estimation under cross-classified sampling with application to a childhood survey," TSE Working Papers 16-659, Toulouse School of Economics (TSE).
   • Hélène Juillard & Guillaume Chauvet & Anne Ruiz-Gazen, 2017. "Estimation Under Cross-Classified Sampling With Application to a Childhood Survey," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 850-858, April.

   Cited by:

   1. Rivest, Louis-Paul & Ebouele, Sergio Ewane, 2020. "Sampling a two dimensional matrix," Computational Statistics & Data Analysis, Elsevier, vol. 149(C).

3. Chakir, Raja & Laurent, Thibault & Ruiz-Gazen, Anne & Thomas-Agnan, Christine & Vignes, Céline, 2016. "Land use predictions on a regular grid at different scales and with easily accessible covariates," TSE Working Papers 16-666, Toulouse School of Economics (TSE).

   Cited by:

   1. Chakir, Raja & Laurent, Thibault & Ruiz-Gazen, Anne & Thomas-Agnan, Christine & Vignes, Céline, 2016. "Spatial scale in land use models: application to the Teruti-Lucas survey," TSE Working Papers 16-667, Toulouse School of Economics (TSE).

4. Laurent, Thibault & Ruiz-Gazen, Anne & Thomas-Agnan, Christine, 2009. "GeoXp: An R Package for Exploratory Spatial Data Analysis," TSE Working Papers 09-099, Toulouse School of Economics (TSE).
   • Laurent, Thibault & Ruiz-Gazen, Anne & Thomas-Agnan, Christine, 2012. "GeoXp: An R Package for Exploratory Spatial Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i02).

   Cited by:

   1. T. Gregory & R. Patuelli, 2013. "Regional Age Structure, Human Capital and Innovation - Is Demographic Ageing Increasing Regional Disparities?," Working Papers wp900, Dipartimento Scienze Economiche, Universita' di Bologna.
      • Terry Gregory & Roberto Patuelli, 2013. "Demographic Ageing and the Polarization of Regions - An Exploratory Space-Time Analysis," Working Paper series 51_13, Rimini Centre for Economic Analysis, revised Feb 2015.
      • Gregory, Terry & Patuelli, Roberto, 2013. "Regional age structure, human capital and innovation: Is demographic ageing increasing regional disparities?," ZEW Discussion Papers 13-057, ZEW - Leibniz Centre for European Economic Research.
      • Terry Gregory & Roberto Patuelli, 2015. "Demographic ageing and the polarization of regions—an exploratory space–time analysis," Environment and Planning A, , vol. 47(5), pages 1192-1210, May.
   2. Payton, Quinn C. & McManus, Michael G. & Weber, Marc H. & Olsen, Anthony R. & Kincaid, Thomas M., 2015. "micromap: A Package for Linked Micromaps," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i02).
   3. Angelos Liontakis & Dimitris Kremmydas, 2013. "Food Inflation in EU: Distribution Analysis and Spatial Effects," Working Papers 2013-3, Agricultural University of Athens, Department Of Agricultural Economics.
   4. de Iaco, Sandra, 2017. "The cgeostat Software for Analyzing Complex-Valued Random Fields," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i05).
   5. Gonzalez-Ollauri, Alejandro & Thomson, Craig S. & Mickovski, Slobodan B., 2020. "Waste to Land (W2L): A novel tool to show and predict the spatial effect of applying biosolids on the environment," Agricultural Systems, Elsevier, vol. 185(C).
   6. de Mouzon, Olivier & Laurent, Thibault & Le Breton, Michel, 2020. "One Man, One Vote Part 2: Measurement of Malapportionment and Disproportionality and the Lorenz Curve," TSE Working Papers 20-1089, Toulouse School of Economics (TSE).
   7. Luc Anselin, 2012. "From SpaceStat to CyberGIS," International Regional Science Review, , vol. 35(2), pages 131-157, April.
   8. Pebesma, Edzer & Bivand, Roger & Ribeiro, Paulo Justiniano, 2015. "Software for Spatial Statistics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i01).

5. Genton, Mark G. & Ruiz-Gazen, Anne, 2009. "Visualizing Influential Observations in Dependent Data," TSE Working Papers 09-051, Toulouse School of Economics (TSE).

   Cited by:

   1. Ronny Vallejos & Felipe Osorio & Diego Mancilla, 2015. "The codispersion map: a graphical tool to visualize the association between two spatial variables," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 298-314, August.
   2. Li, Hongfei & Calder, Catherine A. & Cressie, Noel, 2012. "One-step estimation of spatial dependence parameters: Properties and extensions of the APLE statistic," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 68-84.
   3. Martínez-Hernández, Israel & Genton, Marc G. & González-Farías, Graciela, 2019. "Robust depth-based estimation of the functional autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 66-79.

6. Aragon, Y. & Haughton, D. & Haughton, J. & Leconte, E. & Malin, E. & Ruiz-Gazen, A. & Thomas-Agnan. C., 1999. "Explaining the Pattern of Regional Unemployment: the Case of the Midi-Pyrenees Region," Papers 99.519, Toulouse - GREMAQ.
   • Éric Malin, 2003. "Explaining the pattern of regional unemployment : the case of the Midi-Pyrénées region," Post-Print halshs-00069665, HAL.

   Cited by:

   1. Victor Montuenga & Roberto Bande & Melchor Fernandez, 2011. "Wage flexibility and local labour markets: homogeneity of the wage curve in Spain," ERSA conference papers ersa11p414, European Regional Science Association.
      • Roberto Bande Ramudo & Melchor Fernández Fernández & Víctor Montuenga Gómez, 2011. "Wage flexibility and local labour markets: homogeneity of the wage curve in Spain," Documentos de trabajo - Analise Economica 0044, IDEGA - Instituto Universitario de Estudios e Desenvolvemento de Galicia.
   2. Roberto Patuelli & Norbert Schanne & Daniel A. Griffith & Peter Nijkamp, 2009. "Persistence of Regional Unemployment: Application of a Spatial Filtering Approach to Local Labour Markets in Germany," Working Paper series 49_09, Rimini Centre for Economic Analysis, revised Nov 2011.
      • Patuelli, Roberto & Schanne, Norbert & Griffith, Daniel A. & Nijkamp, Peter, 2011. "Persistence of regional unemployment : Application of a spatial filtering approach to local labour markets in Germany," IAB-Discussion Paper 201103, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
      • R. Patuelli & N. Schanne & D. A. Griffith & P. Nijkamp, 2011. "Persistence of Regional Unemployment: Application of a Spatial Filtering Approach to Local Labour Markets in Germany," Working Papers wp743, Dipartimento Scienze Economiche, Universita' di Bologna.
      • Roberto Patuelli & Norbert Schanne & Daniel A. Griffith & Peter Nijkamp, 2010. "Persistent Disparities in Regional Unemployment: Application of a Spatial Filtering Approach to Local Labour Markets in Germany," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 1001, USI Università della Svizzera italiana.
      • Patuelli, R. & Schanne, N. & Griffith, D.A. & Nijkamp, P., 2010. "Persistent disparities in regional unemployment: Application of a spatial filtering approach to local labour markets in Germany," Serie Research Memoranda 0001, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
      • Roberto Patuelli & Norbert Schanne & Daniel A. Griffith & Peter Nijkamp, 2012. "Persistence Of Regional Unemployment: Application Of A Spatial Filtering Approach To Local Labor Markets In Germany," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 300-323, May.
   3. Cracolici, M. Francesca & Cuffaro, Miranda & Nijkamp, Peter, 2007. "Geographical distribution of unemployment: an analysis of provincial differences in Italy," Serie Research Memoranda 0001, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
      • Maria Francesca Cracolici & Miranda Cuffaro & Peter Nijkamp, 2007. "Geographical Distribution of Unemployment: An Analysis of Provincial Differences in Italy," Tinbergen Institute Discussion Papers 07-065/3, Tinbergen Institute.
      • Maria Francesca Cracolici & Miranda Cuffaro & Peter Nijkamp, 2007. "Geographical Distribution of Unemployment: An Analysis of Provincial Differences in Italy," Growth and Change, Wiley Blackwell, vol. 38(4), pages 649-670, December.
   4. Franziska Lottmann, 2012. "Explaining regional unemployment differences in Germany: a spatial panel data analysis," SFB 649 Discussion Papers SFB649DP2012-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
   5. Sarantis LOLOS & Evangelia PAPAPETROU, 2012. "Unemployment disparities and persistence Assessing the evidence from Greek regions, 1981-2008," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 12(1), pages 69-90.
   6. Natalia PRESSMAN & Vadim KLEPFISH, 2008. "Regional Unemployment Rate Convergence in Israel," EcoMod2008 23800110, EcoMod.
   7. Olga Demidova & Marcello Signorelli, 2010. "The Impact of Crises on Youth Unemployment of Russian Regions: An Empirical Analysis," Quaderni del Dipartimento di Economia, Finanza e Statistica 78/2010, Università di Perugia, Dipartimento Economia.
   8. Román Mínguez & María L. & Roberto Basile, 2016. "Spatio-Temporal Autoregressive Semiparametric Model for the analysis of regional economic data," Working Papers LuissLab 16126, Dipartimento di Economia e Finanza, LUISS Guido Carli.
   9. Michel Blanc & François Hild, 2008. "Analyse des marchés locaux du travail : du chômage à l'emploi," Économie et Statistique, Programme National Persée, vol. 415(1), pages 45-60.
   10. Ana Maria DIAZ ESCOBAR, 2011. "Spatial Unemployment Differentials in Colombia," LIDAM Discussion Papers IRES 2011014, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
       • Ana María Díaz, 2016. "Spatial Unemployment Differentials in Colombia," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 76, February.
   11. Cristiano Perugini & Marcello Signorelli, 2007. "Labour Market Performance Differentials and Dynamics in EU-15 Countries and Regions," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 4(2), pages 209-262, September.
   12. Emmanuel Duguet & Yannick L'horty & Florent Sari, 2023. "Agglomeration effects and unemployment to work: Evidence from French data," Papers in Regional Science, Wiley Blackwell, vol. 102(1), pages 129-166, February.
   13. Semerikova, Elena, 2014. "Unemployment in East and West Germany: Spatial panel data analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 35(3), pages 107-132.
   14. Franziska Lottmann, 2012. "Regional Unemployment in Germany: a spatial panel data analysis," ERSA conference papers ersa12p53, European Regional Science Association.
   15. Laura Helena KIVI & Tiiu PAAS, 2021. "Spatial interactions of employment in European labour markets," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 12, pages 196-211, August.
   16. Cristiano Perugini & Marcello Signorelli, 2010. "Youth labour market performance in European regions," Economic Change and Restructuring, Springer, vol. 43(2), pages 151-185, May.
   17. Semerikova, Elena & Demidova, Olga, 2016. "Using spatial econometric models for regional unemployment forecasting," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 43, pages 29-51.
   18. Laura Helena Kivi, 2019. "Spatial Interactions Of Regional Labour Markets In Europe," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 116, Faculty of Economics and Business Administration, University of Tartu (Estonia).
   19. del Campo, Cristina & Monteiro, Carlos M.F. & Soares, Joao Oliveira, 2008. "The European regional policy and the socio-economic diversity of European regions: A multivariate analysis," European Journal of Operational Research, Elsevier, vol. 187(2), pages 600-612, June.
   20. Román Mínguez & Roberto Basile & María Durbán, 2020. "An alternative semiparametric model for spatial panel data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(4), pages 669-708, December.
   21. Maria Cracolici & Miranda Cuffaro & Peter Nijkamp, 2009. "A spatial analysis on Italian unemployment differences," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(2), pages 275-291, July.
   22. Nigel Driffield & Karl Taylor, 2006. "Wage Spillovers, Inter-regional Effects and the Impact of Inward Investment," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(2), pages 187-205.
   23. Mark Trede & Michael Zimmermann, 2020. "Regional labour migration - Stylized facts for Germany," CQE Working Papers 9320, Center for Quantitative Economics (CQE), University of Muenster.
   24. Raymond J. G. M. Florax & Arno J. Van der Vlist, 2003. "Spatial Econometric Data Analysis: Moving Beyond Traditional Models," International Regional Science Review, , vol. 26(3), pages 223-243, July.

Articles

1. Archimbaud, Aurore & Nordhausen, Klaus & Ruiz-Gazen, Anne, 2018. "ICS for multivariate outlier detection with application to quality control," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 184-199.

   Cited by:

   1. Loperfido, Nicola, 2021. "Some theoretical properties of two kurtosis matrices, with application to invariant coordinate selection," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
   2. Nordhausen, Klaus & Ruiz-Gazen, Anne, 2021. "On the usage of joint diagonalization in multivariate statistics," TSE Working Papers 21-1268, Toulouse School of Economics (TSE).
   3. Nordhausen, Klaus & Ruiz-Gazen, Anne, 2022. "On the usage of joint diagonalization in multivariate statistics," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
   4. Klaus Nordhausen & Anne Ruiz-Gazen, 2022. "On the usage of joint diagonalization in multivariate statistics," Post-Print hal-04296111, HAL.
   5. Archimbaud, Aurore & Boulfani, Fériel & Gendre, Xavier & Nordhausen, Klaus & Ruiz-Gazen, Anne & Virta, Joni, 2021. "ICS for multivariate functional anomaly detection with applications to predictive maintenance and quality control," TSE Working Papers 21-1182, Toulouse School of Economics (TSE), revised Mar 2022.
   6. Ruiz-Gazen, Anne & Thomas-Agnan, Christine & Laurent, Thibault & Mondon, Camille, 2022. "Detecting outliers in compositional data using Invariant Coordinate Selection," TSE Working Papers 22-1320, Toulouse School of Economics (TSE).
      • Anne Ruiz-Gazen & Christine Thomas-Agnan & Thibault Laurent & Camille Mondon, 2023. "Detecting outliers in compositional data using Invariant coordinate selection," Post-Print hal-04216540, HAL.

2. Hélène Juillard & Guillaume Chauvet & Anne Ruiz-Gazen, 2017. "Estimation Under Cross-Classified Sampling With Application to a Childhood Survey," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 850-858, April.
   • Juillard, Hélène & Chauvet, Guillaume & Ruiz-Gazen, Anne, 2016. "Estimation under cross-classified sampling with application to a childhood survey," TSE Working Papers 16-659, Toulouse School of Economics (TSE).
   See citations under working paper version above.
3. Peter Filzmoser & Anne Ruiz-Gazen & Christine Thomas-Agnan, 2014. "Identification of local multivariate outliers," Statistical Papers, Springer, vol. 55(1), pages 29-47, February.

   Cited by:

   1. Mohammed Attouch & Ali Laksaci & Nafissa Messabihi, 2017. "Nonparametric relative error regression for spatial random variables," Statistical Papers, Springer, vol. 58(4), pages 987-1008, December.
   2. Brenton R. Clarke & Andrew Grose, 2023. "A further study comparing forward search multivariate outlier methods including ATLA with an application to clustering," Statistical Papers, Springer, vol. 64(2), pages 395-420, April.
   3. Andrea Cerioli & Marco Riani & Anthony C. Atkinson & Aldo Corbellini, 2018. "Rejoinder to the discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(4), pages 661-666, December.
   4. Fernanda De Bastiani & Audrey Mariz de Aquino Cysneiros & Miguel Uribe-Opazo & Manuel Galea, 2015. "Influence diagnostics in elliptical spatial linear models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(2), pages 322-340, June.
   5. Tarr, G. & Müller, S. & Weber, N.C., 2016. "Robust estimation of precision matrices under cellwise contamination," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 404-420.

4. Camelia Goga & Anne Ruiz-Gazen, 2014. "Efficient estimation of non-linear finite population parameters by using non-parametrics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 113-140, January.

   Cited by:

   1. Goga, Camelia & Ruiz-Gazen, Anne, 2019. "Improving the Estimation of the Odds Ratio in Sampling Surveys using Auxiliary Information," TSE Working Papers 19-1000, Toulouse School of Economics (TSE), revised Jul 2020.
   2. Sumanta Adhya & Banerjee, Tathagata & Chattopadhyay, Gouranga, 2015. "A Note on Estimating Variance of Finite Population Distribution Function," IIMA Working Papers WP2015-08-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
   3. Zhao, Puying & Haziza, David & Wu, Changbao, 2020. "Survey weighted estimating equation inference with nuisance functionals," Journal of Econometrics, Elsevier, vol. 216(2), pages 516-536.

5. J.-F. Beaumont & D. Haziza & A. Ruiz-Gazen, 2013. "A unified approach to robust estimation in finite population sampling," Biometrika, Biometrika Trust, vol. 100(3), pages 555-569.

   Cited by:

   1. Mulry Mary H. & Kaputa Stephen & Thompson Katherine J., 2018. "Setting M-Estimation Parameters for Detection and Treatment of Influential Values," Journal of Official Statistics, Sciendo, vol. 34(2), pages 483-501, June.
   2. Cantoni, Eva & de Luna, Xavier, 2020. "Semiparametric inference with missing data: Robustness to outliers and model misspecification," Econometrics and Statistics, Elsevier, vol. 16(C), pages 108-120.
   3. Martínez-Ovando Juan Carlos & Olivares-Guzmán Sergio I. & Roldán-Rodríguez Adriana, 2014. "Predictive Inference on Finite Populations Segmented in Planned and Unplanned Domains," Working Papers 2014-04, Banco de México.
   4. Valéry Dongmo Jiongo & Pierre Nguimkeu, 2018. "Bootstrapping Mean Squared Errors of Robust Small-Area Estimators: Application to the Method-of-Payments Data," Staff Working Papers 18-28, Bank of Canada.
   5. Valéry Dongmo Jiongo, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Estimation of the Total Private Cost for Large Businesses," Technical Reports 110, Bank of Canada.
   6. Barranco-Chamorro, I. & Jiménez-Gamero, M.D. & Mayor-Gallego, J.A. & Moreno-Rebollo, J.L., 2015. "A case-deletion diagnostic for penalized calibration estimators and BLUP under linear mixed models in survey sampling," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 18-33.
   7. Elena Castilla & Abhik Ghosh & Nirian Martin & Leandro Pardo, 2021. "Robust semiparametric inference for polytomous logistic regression with complex survey design," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 701-734, September.
   8. Schmid, Timo & Tzavidis, Nikos & Münnich, Ralf & Chambers, Ray, 2015. "Outlier robust small area estimation under spatial correlation," Discussion Papers 2015/8, Free University Berlin, School of Business & Economics.

6. Laurent, Thibault & Ruiz-Gazen, Anne & Thomas-Agnan, Christine, 2012. "GeoXp: An R Package for Exploratory Spatial Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i02).
   • Laurent, Thibault & Ruiz-Gazen, Anne & Thomas-Agnan, Christine, 2009. "GeoXp: An R Package for Exploratory Spatial Data Analysis," TSE Working Papers 09-099, Toulouse School of Economics (TSE).
   See citations under working paper version above.
7. Christophe Croux & Mohammed Fekri & Anne Ruiz-Gazen, 2010. "Fast and robust estimation of the multivariate errors in variables model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(2), pages 286-303, August.

   Cited by:

   1. Thi Huong An Nguyen & Anne Ruiz-Gazen & Christine Thomas-Agnan & Thibault Laurent, 2019. "Multivariate Student versus Multivariate Gaussian Regression Models with Application to Finance," JRFM, MDPI, vol. 12(1), pages 1-21, February.
   2. Ana M. Bianco & Paula M. Spano, 2019. "Robust inference for nonlinear regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 369-398, June.
   3. Bianco, Ana M. & Spano, Paula M., 2017. "Robust estimation in partially linear errors-in-variables models," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 46-64.

8. C. Goga & J.-C. Deville & A. Ruiz-Gazen, 2009. "Use of functionals in linearization and composite estimation with application to two-sample survey data," Biometrika, Biometrika Trust, vol. 96(3), pages 691-709.

   Cited by:

   1. Wang, Jianqiang C., 2012. "Sample distribution function based goodness-of-fit test for complex surveys," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 664-679.
   2. Yves G. Berger & Emilio L. Escobar, 2017. "Variance Estimation of Imputed Estimators of Change for Repeated Rotating Surveys," International Statistical Review, International Statistical Institute, vol. 85(3), pages 421-438, December.
   3. Dioggban Jakperik & Romanus Otieno Odhiambo & George Otieno Orwa, 2019. "Inference on poverty indicators for Ghana," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(1), pages 1-4.

9. Fekri, M. & Ruiz-Gazen, A., 2006. "Robust estimation in the simple errors-in-variables model," Statistics & Probability Letters, Elsevier, vol. 76(16), pages 1741-1747, October.

   Cited by:

   1. Eric Blankmeyer, 2018. "Measurement Errors as Bad Leverage Points," Papers 1807.02814, arXiv.org, revised Mar 2020.

10. Croux, Christophe & Ruiz-Gazen, Anne, 2005. "High breakdown estimators for principal components: the projection-pursuit approach revisited," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 206-226, July.

    Cited by:

    1. Fritz, H. & Filzmoser, P. & Croux, C., 2010. "A Comparison of Algorithms for the Multivariate L1-Median," Discussion Paper 2010-106, Tilburg University, Center for Economic Research.
       • Heinrich Fritz & Peter Filzmoser & Christophe Croux, 2012. "A comparison of algorithms for the multivariate L 1 -median," Computational Statistics, Springer, vol. 27(3), pages 393-410, September.
    2. Brooks, J.P. & Dulá, J.H. & Boone, E.L., 2013. "A pure L1-norm principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 83-98.
    3. Sven Serneels, 2019. "Projection pursuit based generalized betas accounting for higher order co-moment effects in financial market analysis," Papers 1908.00141, arXiv.org.
    4. Kalogridis, Ioannis & Van Aelst, Stefan, 2019. "Robust functional regression based on principal components," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 393-415.
    5. Hyndman, Rob J. & Shahid Ullah, Md., 2007. "Robust forecasting of mortality and fertility rates: A functional data approach," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4942-4956, June.
       • Rob J. Hyndman & Md. Shahid Ullah, 2005. "Robust forecasting of mortality and fertility rates: a functional data approach," Monash Econometrics and Business Statistics Working Papers 2/05, Monash University, Department of Econometrics and Business Statistics.
    6. Debruyne, Michiel & Hubert, Mia & Van Horebeek, Johan, 2010. "Detecting influential observations in Kernel PCA," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3007-3019, December.
    7. Choulakian, V. & Allard, J. & Almhana, J., 2006. "Robust centroid method," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 737-746, November.
    8. Jiménez Recaredo, Raúl José & Elías Fernández, Antonio, 2017. "Prediction Bands for Functional Data Based on Depth Measures," DES - Working Papers. Statistics and Econometrics. WS 24606, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Kondylis, Athanassios & Hadi, Ali S., 2006. "Derived components regression using the BACON algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 556-569, November.
    10. Luca Greco & Alessio Farcomeni, 2016. "A plug-in approach to sparse and robust principal component analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 449-481, September.
    11. Pires, Ana M. & Branco, João A., 2010. "Projection-pursuit approach to robust linear discriminant analysis," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2464-2485, November.
    12. Lanius, Vivian & Gather, Ursula, 2010. "Robust online signal extraction from multivariate time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 966-975, April.
    13. Lanius, Vivian & Gather, Ursula, 2007. "Robust online signal extraction from multivariate time series," Technical Reports 2007,38, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    14. Todorov, Valentin & Filzmoser, Peter, 2009. "An Object-Oriented Framework for Robust Multivariate Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i03).
    15. Bali, Juan Lucas & Boente, Graciela, 2015. "Influence function of projection-pursuit principal components for functional data," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 173-199.
    16. Lee, Seokho & Shin, Hyejin & Billor, Nedret, 2013. "M-type smoothing spline estimators for principal functions," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 89-100.
    17. Stephane Heritier & Maria-Pia Victoria-Feser, 2018. "Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(4), pages 595-602, December.
    18. Ulrike Genschel, 2018. "The Effect of Data Contamination in Sliced Inverse Regression and Finite Sample Breakdown Point," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 28-58, February.
    19. Rob J. Hyndman & Han Lin Shang, 2008. "Rainbow plots, Bagplots and Boxplots for Functional Data," Monash Econometrics and Business Statistics Working Papers 9/08, Monash University, Department of Econometrics and Business Statistics.
    20. Hubert, Mia & Rousseeuw, Peter & Verdonck, Tim, 2009. "Robust PCA for skewed data and its outlier map," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2264-2274, April.
    21. Claudio Agostinelli & Ana M. Bianco & Graciela Boente, 2020. "Robust estimation in single-index models when the errors have a unimodal density with unknown nuisance parameter," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 855-893, June.
    22. Serneels, Sven & Verdonck, Tim, 2008. "Principal component analysis for data containing outliers and missing elements," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1712-1727, January.
    23. Hervé Cardot & Antoine Godichon-Baggioni, 2017. "Fast estimation of the median covariation matrix with application to online robust principal components analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(3), pages 461-480, September.
    24. Bali, Juan Lucas & Boente, Graciela, 2014. "Consistency of a numerical approximation to the first principal component projection pursuit estimator," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 181-191.
    25. Graciela Boente & Matías Salibian-Barrera, 2015. "S -Estimators for Functional Principal Component Analysis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1100-1111, September.
    26. Cevallos-Valdiviezo, Holger & Van Aelst, Stefan, 2019. "Fast computation of robust subspace estimators," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 171-185.
    27. Bali, Juan Lucas & Boente, Graciela, 2017. "Robust estimators under a functional common principal components model," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 424-440.
    28. Mani Bayani, 2021. "Robust PCA Synthetic Control," Papers 2108.12542, arXiv.org, revised Oct 2021.
    29. Stephan Morgenthaler, 2007. "A survey of robust statistics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 271-293, February.
    30. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2013. "Efficient R-Estimation of Principal and Common Principal Components," Working Papers ECARES ECARES 2013-18, ULB -- Universite Libre de Bruxelles.
        • Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2014. "Efficient R-Estimation of Principal and Common Principal Components," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1071-1083, September.
    31. B. Barış Alkan, 2016. "Robust Principal Component Analysis Based on Modified Minimum Covariance Determinant in the Presence of Outliers," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 4(2), pages 85-94, September.
    32. Serneels, Sven & Verdonck, Tim, 2009. "Principal component regression for data containing outliers and missing elements," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3855-3863, September.
    33. Graciela Boente & Frank Critchley & Liliana Orellana, 2007. "Influence functions of two families of robust estimators under proportional scatter matrices," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 295-327, February.
    34. Václav Plevka & Pieter Segaert & Chris M. J. Tampère & Mia Hubert, 2016. "Analysis of travel activity determinants using robust statistics," Transportation, Springer, vol. 43(6), pages 979-996, November.
    35. Boente, Graciela & Molina, Julieta & Sued, Mariela, 2010. "On the asymptotic behavior of general projection-pursuit estimators under the common principal components model," Statistics & Probability Letters, Elsevier, vol. 80(3-4), pages 228-235, February.
    36. Hong, David & Balzano, Laura & Fessler, Jeffrey A., 2018. "Asymptotic performance of PCA for high-dimensional heteroscedastic data," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 435-452.

11. Fekri, M. & Ruiz-Gazen, A., 2004. "Robust weighted orthogonal regression in the errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 88(1), pages 89-108, January.

    Cited by:

    1. Fekri, M. & Ruiz-Gazen, A., 2006. "Robust estimation in the simple errors-in-variables model," Statistics & Probability Letters, Elsevier, vol. 76(16), pages 1741-1747, October.
    2. Cator, Eric A. & Lopuhaä, Hendrik P., 2010. "Asymptotic expansion of the minimum covariance determinant estimators," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2372-2388, November.
    3. Eric Blankmeyer, 2018. "Measurement Errors as Bad Leverage Points," Papers 1807.02814, arXiv.org, revised Mar 2020.
    4. Bianco, Ana M. & Spano, Paula M., 2017. "Robust estimation in partially linear errors-in-variables models," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 46-64.
    5. Kang-Mo Jung, 2007. "Least Trimmed Squares Estimator in the Errors-in-Variables Model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(3), pages 331-338.

12. Caussinus, H. & Fekri, M. & Hakam, S. & Ruiz-Gazen, A., 2003. "A monitoring display of multivariate outliers," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 237-252, October.

    Cited by:

    1. Nordhausen, Klaus & Ruiz-Gazen, Anne, 2021. "On the usage of joint diagonalization in multivariate statistics," TSE Working Papers 21-1268, Toulouse School of Economics (TSE).
    2. Nordhausen, Klaus & Ruiz-Gazen, Anne, 2022. "On the usage of joint diagonalization in multivariate statistics," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    3. Salem Reyen & John Miller & Edward Wegman, 2009. "Separating a mixture of two normals with proportional covariances," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 70(3), pages 297-314, November.
    4. Archimbaud, Aurore & Nordhausen, Klaus & Ruiz-Gazen, Anne, 2018. "ICS for multivariate outlier detection with application to quality control," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 184-199.
    5. Klaus Nordhausen & Anne Ruiz-Gazen, 2022. "On the usage of joint diagonalization in multivariate statistics," Post-Print hal-04296111, HAL.
    6. David E. Tyler & Frank Critchley & Lutz Dümbgen & Hannu Oja, 2009. "Invariant co‐ordinate selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 549-592, June.
    7. Laurent, Thibault & Ruiz-Gazen, Anne & Thomas-Agnan, Christine, 2009. "GeoXp: An R Package for Exploratory Spatial Data Analysis," TSE Working Papers 09-099, Toulouse School of Economics (TSE).
       • Laurent, Thibault & Ruiz-Gazen, Anne & Thomas-Agnan, Christine, 2012. "GeoXp: An R Package for Exploratory Spatial Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i02).

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 5 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-AGR: Agricultural Economics (2) 2016-07-09 2016-07-16
2. NEP-GEO: Economic Geography (2) 2010-05-22 2016-07-09
3. NEP-ECM: Econometrics (1) 2010-05-22
4. NEP-FOR: Forecasting (1) 2016-07-16
5. NEP-GER: German Papers (1) 2016-07-16
6. NEP-POL: Positive Political Economics (1) 2018-10-22
7. NEP-URE: Urban and Real Estate Economics (1) 2010-05-22

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Anne Ruiz-Gazen should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.