References in zbMATH (referenced in 33 articles , 1 standard article )

Showing results 1 to 20 of 33.
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  1. Fitzpatrick, Trevor; Mues, Christophe: How can lenders prosper? Comparing machine learning approaches to identify profitable peer-to-peer loan investments (2021)
  2. Ju, Xiaomeng; Salibián-Barrera, Matías: Robust boosting for regression problems (2021)
  3. Tamhane, Ajit C.: Predictive analytics: parametric models for regression and classification using R (2021)
  4. Bhaumik, Dulal K.; Nordgren, Rachel K.: Prediction and calibration for multiple correlated variables (2019)
  5. Cerqueira, Vitor; Torgo, Luís; Pinto, Fábio; Soares, Carlos: Arbitrage of forecasting experts (2019)
  6. Sergio Venturini, Mehmet Mehmetoglu: plssem: A Stata Package for Structural Equation Modeling with Partial Least Squares (2019) not zbMATH
  7. Kawasumi-Kita, Aiko; Ohtsuka, Daisuke; Morishita, Yoshihiro: Morphometric staging of organ development based on cross sectional images (2018)
  8. Mair, Patrick: Modern psychometrics with R (2018)
  9. Stéphanie Bougeard; Stéphane Dray: Supervised Multiblock Analysis in R with the ade4 Package (2018) not zbMATH
  10. Cunningham, Erica; Ciampi, Antonio; Joober, Ridha; Labbe, Aurélie: Estimating and correcting optimism bias in multivariate PLS regression: application to the study of the association between single nucleotide polymorphisms and multivariate traits in attention deficit hyperactivity disorder (2016)
  11. De Niz, Carlos; Rahman, Raziur; Zhao, Xiangyuan; Pal, Ranadip: Algorithms for drug sensitivity prediction (2016)
  12. Faisal, Muhammad; Futschik, Andreas; Hussain, Ijaz; Moemen, Mitwali Abd-El.: Choosing summary statistics by least angle regression for approximate Bayesian computation (2016)
  13. Marlies Vervloet; Henk Kiers; Wim Van den Noortgate; Eva Ceulemans: PCovR: An R Package for Principal Covariates Regression (2015) not zbMATH
  14. Martin Bilodeau; Pierre Micheaux; Smail Mahdi: The R Package groc for Generalized Regression on Orthogonal Components (2015) not zbMATH
  15. Shahriari, Shirin; Faria, Susana; Gonçalves, A. Manuela: Variable selection methods in high-dimensional regression -- a simulation study (2015)
  16. Cristóbal Fresno; Mónica Balzarini; Elmer Fernández: lmdme: Linear Models on Designed Multivariate Experiments in R (2014) not zbMATH
  17. Faraway, Julian J.: Regression for non-Euclidean data using distance matrices (2014)
  18. Shah, Jasmit; Datta, Somnath; Datta, Susmita: A multi-loss super regression learner (MSRL) with application to survival prediction using proteomics (2014)
  19. Blum, M. G. B.; Nunes, M. A.; Prangle, D.; Sisson, S. A.: A comparative review of dimension reduction methods in approximate Bayesian computation (2013)
  20. Kuhn, Max; Johnson, Kjell: Applied predictive modeling (2013)

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