default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDStatistical Methods and Applications, Volume 28
Volume 28, Number 1, March 2019
- Roberto Benedetti
, Maria Simona Andreano, Federica Piersimoni:
Sample selection when a multivariate set of size measures is available. 1-25 - Adelchi Azzalini, Hyoung-Moon Kim, Hea-Jung Kim:
Sample selection models for discrete and other non-Gaussian response variables. 27-56 - Thomas Suesse, Ivy Liu:
Mantel-Haenszel estimators of a common odds ratio for multiple response data. 57-76 - Patrick Marsh:
Nonparametric series density estimation and testing. 77-99 - Patrick Marsh:
Correction to: Nonparametric series density estimation and testing. 101 - Michela Battauz:
On Wald tests for differential item functioning detection. 103-118 - Fabio Bellini, Ilia Negri, Mariya Pyatkova:
Backtesting VaR and expectiles with realized scores. 119-142 - Lu Deng, Wendy Lou, Nicholas Mitsakakis:
Modeling right-censored medical cost data in regression and the effects of covariates. 143-155 - Neska El Haouij, Jean-Michel Poggi, Raja Ghozi, Sylvie Sevestre-Ghalila, Mériem Jaïdane:
Random forest-based approach for physiological functional variable selection for driver's stress level classification. 157-185
Volume 28, Number 3, September 2019
- Tommaso Proietti:
Editorial. 385-387 - Domenico Piccolo, Rosaria Simone:
The class of cub models: statistical foundations, inferential issues and empirical evidence. 389-435 - Francesco Bartolucci, Fulvia Pennoni:
Comment on: The class of CUB models: statistical foundations, inferential issues and empirical evidence. 437-439 - Roberto Colombi, Sabrina Giordano, Anna Gottard:
Discussion of "The class of CUB models: statistical foundations, inferential issues and empirical evidence". 441-444 - Alan Agresti, Maria Kateri:
The class of CUB models: statistical foundations, inferential issues and empirical evidence. 445-449 - Tommaso Proietti:
Discussion of The class of CUB models: statistical foundations, inferential issues and empirical evidence - by D. Piccolo and R. Simone. 451-456 - Ron S. Kenett:
A review of: The class of CUB models: statistical foundations, inferential issues and empirical evidence by Domenico Piccolo and Rosaria Simone. 457-458 - Leonardo Grilli, Carla Rampichini:
Discussion of 'The class of CUB models: statistical foundations, inferential issues and empirical evidence' by Domenico Piccolo and Rosaria Simone. 459-463 - Marica Manisera, Paola Zuccolotto:
Discussion of "The class of cub models: statistical foundations, inferential issues and empirical evidence" by Domenico Piccolo and Rosaria Simone. 465-470 - Gerhard Tutz:
Comments on The class of cub models: statistical foundations, inferential issues and empirical evidence by D. Piccolo and R. Simone. 471-475 - Domenico Piccolo, Rosaria Simone:
Rejoinder to the discussion of "The class of cub models: statistical foundations, inferential issues and empirical evidence". 477-493 - Haruhiko Ogasawara:
The multiple Cantelli inequalities. 495-506 - Rainer Hirk, Kurt Hornik, Laura Vana:
Multivariate ordinal regression models: an analysis of corporate credit ratings. 507-539 - Guido Bulligan, Lorenzo Burlon, Davide Delle Monache, Andrea Silvestrini:
Real and financial cycles: estimates using unobserved component models for the Italian economy. 541-569
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-11-07 20:33 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
