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Publication search results
found 475 matches
- 2019
- Alan Agresti, Maria Kateri:
The class of CUB models: statistical foundations, inferential issues and empirical evidence. Stat. Methods Appl. 28(3): 445-449 (2019) - Adelchi Azzalini, Hyoung-Moon Kim, Hea-Jung Kim:
Sample selection models for discrete and other non-Gaussian response variables. Stat. Methods Appl. 28(1): 27-56 (2019) - Francesco Bartolucci, Fulvia Pennoni:
Comment on: The class of CUB models: statistical foundations, inferential issues and empirical evidence. Stat. Methods Appl. 28(3): 437-439 (2019) - Michela Battauz:
On Wald tests for differential item functioning detection. Stat. Methods Appl. 28(1): 103-118 (2019) - Fabio Bellini, Ilia Negri, Mariya Pyatkova:
Backtesting VaR and expectiles with realized scores. Stat. Methods Appl. 28(1): 119-142 (2019) - Roberto Benedetti, Maria Simona Andreano, Federica Piersimoni:
Sample selection when a multivariate set of size measures is available. Stat. Methods Appl. 28(1): 1-25 (2019) - Guido Bulligan, Lorenzo Burlon, Davide Delle Monache, Andrea Silvestrini:
Real and financial cycles: estimates using unobserved component models for the Italian economy. Stat. Methods Appl. 28(3): 541-569 (2019) - Roberto Colombi, Sabrina Giordano, Anna Gottard:
Discussion of "The class of CUB models: statistical foundations, inferential issues and empirical evidence". Stat. Methods Appl. 28(3): 441-444 (2019) - Lu Deng, Wendy Lou, Nicholas Mitsakakis:
Modeling right-censored medical cost data in regression and the effects of covariates. Stat. Methods Appl. 28(1): 143-155 (2019) - Leonardo Grilli, Carla Rampichini:
Discussion of 'The class of CUB models: statistical foundations, inferential issues and empirical evidence' by Domenico Piccolo and Rosaria Simone. Stat. Methods Appl. 28(3): 459-463 (2019) - 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. Stat. Methods Appl. 28(1): 157-185 (2019) - Rainer Hirk, Kurt Hornik, Laura Vana:
Multivariate ordinal regression models: an analysis of corporate credit ratings. Stat. Methods Appl. 28(3): 507-539 (2019) - Ron S. Kenett:
A review of: The class of CUB models: statistical foundations, inferential issues and empirical evidence by Domenico Piccolo and Rosaria Simone. Stat. Methods Appl. 28(3): 457-458 (2019) - Marica Manisera, Paola Zuccolotto:
Discussion of "The class of cub models: statistical foundations, inferential issues and empirical evidence" by Domenico Piccolo and Rosaria Simone. Stat. Methods Appl. 28(3): 465-470 (2019) - Patrick Marsh:
Nonparametric series density estimation and testing. Stat. Methods Appl. 28(1): 77-99 (2019) - Patrick Marsh:
Correction to: Nonparametric series density estimation and testing. Stat. Methods Appl. 28(1): 101 (2019) - Haruhiko Ogasawara:
The multiple Cantelli inequalities. Stat. Methods Appl. 28(3): 495-506 (2019) - Domenico Piccolo, Rosaria Simone:
The class of cub models: statistical foundations, inferential issues and empirical evidence. Stat. Methods Appl. 28(3): 389-435 (2019) - Domenico Piccolo, Rosaria Simone:
Rejoinder to the discussion of "The class of cub models: statistical foundations, inferential issues and empirical evidence". Stat. Methods Appl. 28(3): 477-493 (2019) - Tommaso Proietti:
Editorial. Stat. Methods Appl. 28(3): 385-387 (2019) - Tommaso Proietti:
Discussion of The class of CUB models: statistical foundations, inferential issues and empirical evidence - by D. Piccolo and R. Simone. Stat. Methods Appl. 28(3): 451-456 (2019) - Thomas Suesse, Ivy Liu:
Mantel-Haenszel estimators of a common odds ratio for multiple response data. Stat. Methods Appl. 28(1): 57-76 (2019) - Gerhard Tutz:
Comments on The class of cub models: statistical foundations, inferential issues and empirical evidence by D. Piccolo and R. Simone. Stat. Methods Appl. 28(3): 471-475 (2019) - 2018
- Ali Aghamohammadi:
Bayesian analysis of dynamic panel data by penalized quantile regression. Stat. Methods Appl. 27(1): 91-108 (2018) - Claudio Agostinelli, Luca Greco:
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. Stat. Methods Appl. 27(4): 609-619 (2018) - Raffaele Argiento, Matteo Ruggiero:
Computational challenges and temporal dependence in Bayesian nonparametric models. Stat. Methods Appl. 27(2): 231-238 (2018) - Lucio Barabesi, Carolina Becatti, Marzia Marcheselli:
The Tempered Discrete Linnik distribution. Stat. Methods Appl. 27(1): 45-68 (2018) - Giulia Barbati, Alessio Farcomeni:
Prognostic assessment of repeatedly measured time-dependent biomarkers, with application to dilated cardiomyopathy. Stat. Methods Appl. 27(3): 545-557 (2018) - Marco Bee, Maria Michela Dickson, Flavio Santi:
Likelihood-based risk estimation for variance-gamma models. Stat. Methods Appl. 27(1): 69-89 (2018) - Andrea Cerioli, Marco Riani, Anthony C. Atkinson, Aldo Corbellini:
The power of monitoring: how to make the most of a contaminated multivariate sample. Stat. Methods Appl. 27(4): 559-587 (2018)
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