Zobrazeno 1 - 10
of 29
pro vyhledávání: '"regressogram"'
Autor:
Pourahmadi, Mohsen
Publikováno v:
International Statistical Review / Revue Internationale de Statistique, 2002 Dec 01. 70(3), 395-417.
Externí odkaz:
https://www.jstor.org/stable/1403864
Publikováno v:
The Annals of Statistics, 2009 Feb 01. 37(1), 157-183.
Externí odkaz:
https://www.jstor.org/stable/25464745
Publikováno v:
Lecture Notes-Monograph Series, 2007 Jan 01. 55, 65-84.
Externí odkaz:
https://www.jstor.org/stable/20461484
Binscatter is very popular in applied microeconomics. It provides a flexible, yet parsimonious way of visualizing and summarizing "big data" in regression settings, and it is often used for informal testing of substantive hypotheses such as linearity
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1687::efc0071b00f51c0973211c8d01509693
https://hdl.handle.net/10419/210733
https://hdl.handle.net/10419/210733
Autor:
Mohlin, Erik
Regression trees are evaluated with respect to mean square error (MSE), mean integrated square error (MISE), and integrated squared error (ISE), as the size of the training sample goes to infinity. The asymptotically MSE- and MISE minimizing (locally
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1687::c2513a5880e86e30e94ec6fb51a87583
https://hdl.handle.net/10419/260241
https://hdl.handle.net/10419/260241
Autor:
Dia, Galaye, Kone, Abdoulaye
We estimate a regression function on a point process by the Tukey regressogram method in a general setting and we give an application in the case of a Risk Process. We show among other things that, in classical Poisson model with parameter r, if W is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::e44fd5d4677c3886bb9fd70adb2f6096
https://hdl.handle.net/10525/2676
https://hdl.handle.net/10525/2676
Autor:
Dia, Galaye
This paper was announced in [4] where we estimated a régression fonction of a accumulated claim fonction on the corresponding accumulated waiting time to predict the ruin arrivai time in the case of a deterministic barrier. This led to an analytic d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______166::7882270f0736372104f22f319cc9690e
https://hal.archives-ouvertes.fr/hal-03615533
https://hal.archives-ouvertes.fr/hal-03615533
Publikováno v:
The Annals of Statistics, 37(1), 157-183. Institute of Mathematical Statistics
Ann. Stat. 37, 157-183 (2009)
Ann. Statist. 37, no. 1 (2009), 157-183
Ann. Stat. 37, 157-183 (2009)
Ann. Statist. 37, no. 1 (2009), 157-183
We study the asymptotics for jump-penalized least squares regression aiming at approximating a regression function by piecewise constant functions. Besides conventional consistency and convergence rates of the estimates in $L^2([0,1))$ our results co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8284257efdddb1af2ab40fac109ee54
https://doi.org/10.1214/07-aos558
https://doi.org/10.1214/07-aos558
Autor:
Arlot, Sylvain, Massart, Pascal
Publikováno v:
Journal of Machine Learning Research
Journal of Machine Learning Research, Microtome Publishing, 2009, 10, pp.245-279
Journal of Machine Learning Research, 2009, 10, pp.245-279
Journal of Machine Learning Research, Microtome Publishing, 2009, 10, pp.245-279
Journal of Machine Learning Research, 2009, 10, pp.245-279
International audience; Penalization procedures often suffer from their dependence on multiplying factors, whose optimal values are either unknown or hard to estimate from the data. We propose a completely data-driven calibration algorithm for this p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb022ff7fec5d0a2fa4473ddd0bec2e2
Autor:
Sylvain Arlot
Publikováno v:
Electronic Journal of Statistics
Electronic Journal of Statistics, Shaker Heights, OH : Institute of Mathematical Statistics, 2009, 3, pp.557--624. ⟨10.1214/08-EJS196⟩
Electron. J. Statist. 3 (2009), 557-624
Electronic Journal of Statistics, 2009, 3, pp.557--624. ⟨10.1214/08-EJS196⟩
Electronic Journal of Statistics, Shaker Heights, OH : Institute of Mathematical Statistics, 2009, 3, pp.557--624. ⟨10.1214/08-EJS196⟩
Electron. J. Statist. 3 (2009), 557-624
Electronic Journal of Statistics, 2009, 3, pp.557--624. ⟨10.1214/08-EJS196⟩
In this paper, a new family of resampling-based penalization procedures for model selection is defined in a general framework. It generalizes several methods, including Efron's bootstrap penalization and the leave-one-out penalization recently propos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::007763a88d85186502f2dfdbc24917e4
http://arxiv.org/abs/math/0701542
http://arxiv.org/abs/math/0701542