References in zbMATH (referenced in 22 articles )

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  1. Ndlovu, Bonginkosi; Melesse, Sileshi; Zewotir, Temesgen: A regression analysis of discrete time competing risks data using a vertical model approach (2022)
  2. Taconeli, Cesar Augusto; de Lara, Idemauro Antonio Rodrigues: Discrete Weibull distribution: different estimation methods under ranked set sampling and simple random sampling (2022)
  3. Dedduwakumara, Dilanka S.; Prendergast, Luke A.; Staudte, Robert G.: An efficient estimator of the parameters of the generalized lambda distribution (2021)
  4. Farzammehr, Mohadeseh Alsadat; Zadkarami, Mohammad Reza; McLachlan, Geoffrey J.: Skew-normal generalized spatial panel data model (2021)
  5. Ownuk, Jamil; Baghishani, Hossein; Nezakati, Ahmad: Heavy or semi-heavy tail, that is the question (2021)
  6. Zheng, Songfeng: KLERC: kernel Lagrangian expectile regression calculator (2021)
  7. Schmid, Matthias; Welchowski, Thomas; Wright, Marvin N.; Berger, Moritz: Discrete-time survival forests with Hellinger distance decision trees (2020)
  8. Das, Ishapathik; Sen, Sumen; Chaganty, N. Rao; Sengupta, Pooja: Regression for doubly inflated multivariate Poisson distributions (2019)
  9. Berger, Moritz; Schmid, Matthias: Semiparametric regression for discrete time-to-event data (2018)
  10. Villa, Cristiano; Rubio, Francisco J.: Objective priors for the number of degrees of freedom of a multivariate (t) distribution and the (t)-copula (2018)
  11. Huang, Alan: Mean-parametrized Conway-Maxwell-Poisson regression models for dispersed counts (2017)
  12. Reto Bürgin; Gilbert Ritschard: Coefficient-Wise Tree-Based Varying Coefficient Regression with vcrpart (2017) not zbMATH
  13. Tutz, Gerhard; Schmid, Matthias: Modeling discrete time-to-event data (2016)
  14. Alexandre Brouste; Masaaki Fukasawa; Hideitsu Hino; Stefano Iacus; Kengo Kamatani; Yuta Koike; Hiroki Masuda; Ryosuke Nomura; Teppei Ogihara; Yasutaka Shimuzu; Masayuki Uchida; Nakahiro Yoshida: The YUIMA Project: A Computational Framework for Simulation and Inference of Stochastic Differential Equations (2014) not zbMATH
  15. Karlsson, Maria; Laitila, Thomas: Finite mixture modeling of censored regression models (2014)
  16. Millo, Giovanni: Maximum likelihood estimation of spatially and serially correlated panels with random effects (2014)
  17. Sáez-Castillo, A. J.; Conde-Sánchez, A.: A hyper-Poisson regression model for overdispersed and underdispersed count data (2013)
  18. Giovanni Millo; Gianfranco Piras: splm: Spatial Panel Data Models in R (2012) not zbMATH
  19. Henderson, Daniel J.; Kumbhakar, Subal C.; Parmeter, Christopher F.: A simple method to visualize results in nonlinear regression models (2012)
  20. Yves Croissant; Giovanni Millo: Panel Data Econometrics in R: The plm Package (2008) not zbMATH

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