On the Exact Finite Sample Distribution of the L1 -FCvM Test Statistic
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Schmid, Friedrich & Trede, Mark, 1995. "A distribution free test for the two sample problem for general alternatives," Computational Statistics & Data Analysis, Elsevier, vol. 20(4), pages 409-419, October.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Alex Imas & Sally Sadoff & Anya Samek, 2017.
"Do People Anticipate Loss Aversion?,"
Management Science, INFORMS, vol. 63(5), pages 1271-1284, May.
- Alex Imas & Sally Sadoff & Anya Samek, 2015. "Do People Anticipate Loss Aversion?," CESifo Working Paper Series 5277, CESifo.
- Alex Imas & Sally Sadoff & Anya Samek, 2015. "Do People Anticipate Loss Aversion," Framed Field Experiments 00415, The Field Experiments Website.
- Jeroen Hinloopen & Rien J.L.M. Wagenvoort & Charles van Marrewijk, 2012. "A k-sample homogeneity test: the Harmonic Weighted Mass index," International Econometric Review (IER), Econometric Research Association, vol. 4(1), pages 17-39, April.
- Magdalena Smyk & Joanna Tyrowicz & Lucas van der Velde, 2021.
"A Cautionary Note on the Reliability of the Online Survey Data: The Case of Wage Indicator,"
Sociological Methods & Research, , vol. 50(1), pages 429-464, February.
- Joanna Tyrowicz & Magdalena Smyk & Lucas van der Velde, 2018. "A cautionary note on the reliability of the online survey data – the case of Wage Indicator," IAAEU Discussion Papers 201805, Institute of Labour Law and Industrial Relations in the European Union (IAAEU).
- Joanna Tyrowicz & Magdalena Smyk & Lucas van der Velde, 2018. "A cautionary note on the reliability of the online survey data - the case of Wage Indicator," GRAPE Working Papers 26, GRAPE Group for Research in Applied Economics.
- Smyk, Magdalena & Tyrowicz, Joanna & van der Velde, Lucas, 2018. "A Cautionary Note on the Reliability of the Online Survey Data: The Case of Wage Indicator," IZA Discussion Papers 11503, Institute of Labor Economics (IZA).
- Kraft, Stefan & Schmid, Friedrich, 2000. "Nonparametric tests based on area-statistics," Discussion Papers in Econometrics and Statistics 2/00, University of Cologne, Institute of Econometrics and Statistics.
- Henze, Norbert & Nikitin, Yakov & Ebner, Bruno, 2009. "Integral distribution-free statistics of Lp-type and their asymptotic comparison," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3426-3438, July.
- Uri Gneezy & John A. List & Jeffrey A. Livingston & Xiangdong Qin & Sally Sadoff & Yang Xu, 2019.
"Measuring Success in Education: The Role of Effort on the Test Itself,"
American Economic Review: Insights, American Economic Association, vol. 1(3), pages 291-308, December.
- Uri Gneezy & John List & Jeffrey Livingston & Xiangdong Qin & Sally Sadoff & Yang Xu, 2017. "Measuring success in education: the role of effort on the test itself," Framed Field Experiments 00614, The Field Experiments Website.
- Uri Gneezy & John A. List & Jeffrey A. Livingston & Sally Sadoff & Xiangdong Qin & Yang Xu, 2017. "Measuring Success in Education: The Role of Effort on the Test Itself," NBER Working Papers 24004, National Bureau of Economic Research, Inc.
- Jeroen Hinloopen & Rien Wagenvoort & Charles van Marrewijk, 2008. "A K-sample Homogeneity Test based on the Quantification of the p-p Plot," Tinbergen Institute Discussion Papers 08-100/1, Tinbergen Institute.
- Angel G. Angelov & Magnus Ekström, 2023. "Tests of stochastic dominance with repeated measurements data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 443-467, September.
- Taylor, C. C. & Zempleni, A., 2004. "Chain plot: a tool for exploiting bivariate temporal structures," Computational Statistics & Data Analysis, Elsevier, vol. 46(1), pages 141-153, May.
- L. Baringhaus & D. Kolbe, 2015. "Two-sample tests based on empirical Hankel transforms," Statistical Papers, Springer, vol. 56(3), pages 597-617, August.
- Jeroen Hinloopen & Rien Wagenvoort, 2010. "Identifying All Distinct Sample P-P Plots, with an Application to the Exact Finite Sample Distribution of the L1-FCvM Test Statistic," Tinbergen Institute Discussion Papers 10-083/1, Tinbergen Institute.
More about this item
Keywords
Sample p-p plot; EDF test; finite sample distribution; limiting distribution;All these keywords.
JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tin:wpaper:20110083. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.