aplore3

aplore3: Datasets from Hosmer, Lemeshow and Sturdivant, ”Applied Logistic Regression” (3rd ed.) This package is a unofficial companion to the textbook ”Applied Logistic Regression” by D.W. Hosmer, S. Lemeshow and R.X. Sturdivant (3rd ed.).

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 64 articles )

Showing results 1 to 20 of 64.
Sorted by year (citations)

1 2 3 4 next

  1. Höppner, Sebastiaan; Baesens, Bart; Verbeke, Wouter; Verdonck, Tim: Instance-dependent cost-sensitive learning for detecting transfer fraud (2022)
  2. Kim, Min-Ho; Lee, Jea-Young: How to construct a nomogram for hypertension using complex sampling data from Korean adults (2022)
  3. Silva, Diego M. B.; Pereira, Gustavo H. A.; Magalhães, Tiago M.: A class of categorization methods for credit scoring models (2022)
  4. Başoğlu Kabran, Fatma; Ünlü, Kamil Demirberk: A two-step machine learning approach to predict S&P 500 bubbles (2021)
  5. Civitelli, Enrico; Lapucci, Matteo; Schoen, Fabio; Sortino, Alessio: An effective procedure for feature subset selection in logistic regression based on information criteria (2021)
  6. Gunnarsson, Björn Rafn; vanden Broucke, Seppe; Baesens, Bart; Óskarsdóttir, María; Lemahieu, Wilfried: Deep learning for credit scoring: do or don’t? (2021)
  7. Krasanakis, Emmanouil; Symeonidis, Andreas: Defining behaviorizeable relations to enable inference in semi-automatic program synthesis (2021)
  8. Pinto, Vimukthini; Sooriyarachchi, Roshini: Comparison of methods of estimation for a goodness of fit test -- an analytical and simulation study (2021)
  9. Whitaker, T.; Beranger, B.; Sisson, S. A.: Logistic regression models for aggregated data (2021)
  10. Yu, Peiran; Pong, Ting Kei; Lu, Zhaosong: Convergence rate analysis of a sequential convex programming method with line search for a class of constrained difference-of-convex optimization problems (2021)
  11. Yu, Tengchao; Wang, Hongqiao; Li, Jinglai: Maximum conditional entropy Hamiltonian Monte Carlo sampler (2021)
  12. Zhang, Xu; Tian, Yahui; Guan, Guoyu; Gel, Yulia R.: Depth-based classification for relational data with multiple attributes (2021)
  13. Zhu, Xuening; Li, Feng; Wang, Hansheng: Least-square approximation for a distributed system (2021)
  14. Brentnall, Adam R.; Cuzick, Jack: Risk models for breast cancer and their validation (2020)
  15. Cui, Chunfeng; Zhang, Kaiqi; Daulbaev, Talgat; Gusak, Julia; Oseledets, Ivan; Zhang, Zheng: Active subspace of neural networks: structural analysis and universal attacks (2020)
  16. Li, Yong; Asar, Yasin; Wu, Jibo: On the stochastic restricted Liu estimator in logistic regression model (2020)
  17. McManus, Scott; Rahman, Azizur; Horta, Ana; Coombes, Jacqueline: Applied Bayesian modeling for assessment of interpretation uncertainty in spatial domains (2020)
  18. Metulini, Rodolfo; Le Carre, Mael: Measuring sport performances under pressure by classification trees with application to basketball shooting (2020)
  19. Naka, Poontavika; Boado-Penas, María del Carmen; Lanot, Gauthier: A multiple state model for the working-age disabled population using cross-sectional data (2020)
  20. Orozco-Acosta, Erick; Llinás-Solano, Humberto; Fonseca-Rodríguez, Javier: Convergence theorems in multinomial saturated and logistic models (2020)

1 2 3 4 next