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Books on the topic 'Median regression, quantile regression'

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Published: 9 March 2023
Last updated: 10 March 2023

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1

Hao, Lingxin, and Daniel Naiman. Quantile Regression. 2455 Teller Road, Thousand Oaks California 91320 United States of America: SAGE Publications, Inc., 2007. http://dx.doi.org/10.4135/9781412985550.

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2

Davino, Cristina, Marilena Furno, and Domenico Vistocco. Quantile Regression. Oxford: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118752685.

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3

Marilena, Furno, and Vistocco Domenico. Quantile Regression. Chichester, UK: John Wiley & Sons Ltd, 2018. http://dx.doi.org/10.1002/9781118863718.

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4

Hao, Lingxin. Quantile regression. Thousand Oaks, Calif: Sage Publications, 2007.

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5

Chernozhukov, Victor. Instrumental variable quantile regression. Cambridge, MA: Massachusetts Institute of Technology, Dept. of Economics, 2006.

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6

Cleophas, Ton J., and Aeilko H. Zwinderman. Quantile Regression in Clinical Research. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82840-0.

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7

McMillen, Daniel P. Quantile Regression for Spatial Data. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-31815-3.

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8

Fitzenberger, Bernd, Roger Koenker, and José A. F. Machado, eds. Economic Applications of Quantile Regression. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-662-11592-3.

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9

Chernozhukov, Victor. Quantile regression with censoring and endogeneity. Cambridge, MA: National Bureau of Economic Research, 2011.

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10

Ling, Wodan. Quantile regression for zero-inflated outcomes. [New York, N.Y.?]: [publisher not identified], 2019.

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11

Chernozhukov, Victor. Finite sample inference for quantile regression models. Cambridge, MA: Massachusetts Institute of Technology, Dept. of Economics, 2006.

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12

Chernozhukov, Victor. Inference on quantile regression process: An alternative. Cambridge, MA: Massachusetts Institute of Technology, Dept. of Economics, 2002.

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13

Koenker, Roger. Quantile regression models for global temperature change. Champaign: University of Illinois at Urbana-Champaign, 1993.

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14

Koenker, Roger W. An interior point algorithm for nonlinear quantile regression / Roger Koenker ; Beum J. Park. Champaign: University of Illinois at Urbana-Champaign, 1992.

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15

Chernozhukov, Victor. L1-Penalized Quantile Regression in High Dimensional Sparse Models. Cambridge, MA: Massachusetts Institute of Technology, Dept. of Economics, 2009.

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16

Engle, R. F. CAViaR: Conditional value at risk by quantile regression. Cambridge, MA: National Bureau of Economic Research, 1999.

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17

Chernozhukov, Victor. Inference for distributional effects using instrumental quantile regression. Cambridge, MA: Massachusetts Institute of Technology, Dept. of Economics, 2002.

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18

Uribe, Jorge M., and Montserrat Guillen. Quantile Regression for Cross-Sectional and Time Series Data. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1.

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19

Chernozhukov, Victor. Simple 3-step censored quantile regression and extramartial affairs. Cambridge, MA: Massachusetts Institute of Technology, Dept. of Economics, 2001.

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20

Krishnamurthy, Chandra Kiran B. The distributional impacts of climate change on Indian agriculture: A quantile regression approach. Chennai, India: Madras School of Economics, 2012.

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21

Arabsheibani, G. R. Human capital and earnings inequality in Brazil, 1988-98: Quantile regression evidence. Washington, D.C: World Bank, 2003.

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22

Angrist, Joshua David. Quantile regression under misspecification with an application to the U.S. wage structure. Cambridge, MA: Massachusetts Institute of Technology, Dept. of Economics, 2004.

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23

Angrist, Joshua David. Quantile regression under misspecification, with an application to the U.S. wage structure. Cambridge, MA: National Bureau of Economic Research, 2004.

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24

Poterba, James M. The distribution of public sector wage premia: New evidence using quantile regression methods. Cambridge, MA: National Bureau of Economic Research, 1994.

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25

Sha, Nanshi. On testing the change-point in the longitudinal bent line quantile regression model. [New York, N.Y.?]: [publisher not identified], 2011.

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26

Sriram, Karthik. A bayesian semiparametric quantile regression model for longitudinal data with application to insurance company costs. Bangalore: Indian Institute of Management Bangalore, 2011.

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27

Sriram, Karthik. Posterior consistency of bayesian quantile regression under a mis-specified likelihood based on asymmetric laplace density. Bangalore: Indian Institute of Management Bangalore, 2011.

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28

Statistics Canada. Analytical Studies Branch., ed. In search of intergenerational credit constraints among men: Quantile versus mean regression tests for binding credit constraints. Ottawa, Ont: Analytical Studies Branch, Statistics Canada, 2001.

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29

Fitzenberger, Bernd. New insights on unemployment duration and post unemployment earnings in Germany: Censored box-cox quantile regression at work. Bonn, Germany: IZA, 2007.

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30

Canada. Statistics Canada. Analytical Studies Branch. In search of intergenerational credit constraints among Canadian men: Quantile versus mean regression tests for binding credit constraints. Ottawa: Statistics Canada, 2001.

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31

C, Sorrell Richard, Holtschlag David J, Michigan. Department of Environmental Quality, Michigan. Department of Natural Resources, and Geological Survey (U.S.), eds. A regression model for computing index flows describing the median flow for the summer month of lowest flow in Michigan. 2nd ed. Reston, Va: U.S. Dept. of the Interior, U.S. Geological Survey, 2011.

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32

Hamilton, David A. A regression model for computing index flows describing the median flow for the summer month of lowest flow in Michigan. Reston, Va: U.S. Dept. of the Interior, U.S. Geological Survey, 2008.

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33

Hamilton, David A. A regression model for computing index flows describing the median flow for the summer month of lowest flow in Michigan. Reston, Va: U.S. Dept. of the Interior, U.S. Geological Survey, 2008.

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34

Wirba, Ebenezer Lemven, Fiennasah Annif' Akem, and Francis Menjo Baye. Scrutinizing the sticky floor/glass ceiling phenomena in the informal labour market in Cameroon: An unconditional quantile regression analysis. 13th ed. UNU-WIDER, 2021. http://dx.doi.org/10.35188/unu-wider/2021/947-1.

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Abstract:
Cameroon’s informal labour market largely harbours female workers, engaged mainly in low-productivity and low-paying jobs. We investigate the sticky floor and glass ceiling phenomena in the informal labour market as a whole and across its segments. We use the 2010 Cameroon labour market survey, employing the recentred influence function and blending the Oaxaca-Ransom and Neuman-Oaxaca decomposition methods. The resulting framework enables us to account for selectivity bias at the mean, resolve the index number problem of the standard decomposition, and examine earnings differentials across the unconditional earnings distribution. We find compelling evidence of a sticky floor phenomenon in the informal labour market manifested essentially among wage earners. Returns to experience mitigate the gender earnings gap at the mean, and 10th and 50th percentiles of the unconditional earnings distribution. Female workers have an unambiguous human-capital-based advantage over their male counterparts at the mean, lower tail, and median of the distribution.
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35

Naiman, Daniel Q., and Lingxin Hao. Quantile Regression. SAGE Publications, Incorporated, 2007.

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36

Quantile Regression. New York: Cambridge University Press, 2005. http://dx.doi.org/10.1017/ccol0521845734.

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37

Koenker, Roger. Quantile Regression. Cambridge University Press, 2010.

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38

Koenker, Roger. Quantile Regression. Cambridge University Press, 2005.

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39

Koenker, Roger. Quantile Regression. Cambridge University Press, 2005.

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40

Koenker, Roger, Andrew Chesher, and Matthew Jackson. Quantile Regression. Cambridge University Press, 2005.

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41

Koenker, Roger, Victor Chernozhukov, Xuming He, and Limin Peng. Handbook of Quantile Regression. Taylor & Francis Group, 2017.

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42

Koenker, Roger, Victor Chernozhukov, Xuming He, and Limin Peng. Handbook of Quantile Regression. Taylor & Francis Group, 2017.

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43

Koenker, Roger, Victor Chernozhukov, Xuming He, and Limin Peng, eds. Handbook of Quantile Regression. Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315120256.

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44

Handbook of Quantile Regression. Taylor & Francis Group, 2017.

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45

Koenker, Roger, Victor Chernozhukov, Xuming He, and Limin Peng. Handbook of Quantile Regression. Taylor & Francis Group, 2017.

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46

Koenker, Roger, Victor Chernozhukov, Xuming He, and Limin Peng. Handbook of Quantile Regression. Taylor & Francis Group, 2017.

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47

Koenker, Roger, Victor Chernozhukov, Xuming He, and Limin Peng. Handbook of Quantile Regression. Taylor & Francis Group, 2020.

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48

Riobe, Charmain. Quantile Regression : Partial Correlation in Psychology: Regression Testing. Independently Published, 2021.

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49

Quantile Regression Theory And Applications. John Wiley & Sons Inc, 2013.

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50

Quantile Regression For Spatial Data. Springer, 2012.

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