References in zbMATH (referenced in 33 articles )

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  1. Zhang, Boya; Gramacy, Robert B.; Johnson, Leah R.; Rose, Kenneth A.; Smith, Eric: Batch-sequential design and heteroskedastic surrogate modeling for delta smelt conservation (2022)
  2. Rodney Sparapani, Charles Spanbauer, Robert McCulloch: Nonparametric Machine Learning and Efficient Computation with Bayesian Additive Regression Trees: The BART R Package (2021) not zbMATH
  3. Esam Mahdi: portes: An R Package for Portmanteau Tests in Time Series Models (2020) arXiv
  4. Seyoon Ko, Hua Zhou, Jin Zhou, Joong-Ho Won: DistStat.jl: Towards Unified Programming for High-Performance Statistical Computing Environments in Julia (2020) arXiv
  5. Agostinelli, Claudio; Valdora, Marina; Yohai, Victor J.: Initial robust estimation in generalized linear models (2019)
  6. Bertolacci, Michael; Cripps, Edward; Rosen, Ori; Lau, John W.; Cripps, Sally: Climate inference on daily rainfall across the Australian continent, 1876--2015 (2019)
  7. Oleksii Pokotylo; Pavlo Mozharovskyi; Rainer Dyckerhoff: Depth and Depth-Based Classification with R Package ddalpha (2019) not zbMATH
  8. Srivastava, Sanvesh; DePalma, Glen; Liu, Chuanhai: An asynchronous distributed expectation maximization algorithm for massive data: the DEM algorithm (2019)
  9. Gallagher, Shannon; Richardson, Lee F.; Ventura, Samuel L.; Eddy, William F.: SPEW: synthetic populations and ecosystems of the world (2018)
  10. Popuri, Sai K.; Raim, Andrew M.; Neerchal, Nagaraj K.; Gobbert, Matthias K.: Parallelizing computation of expected values in recombinant binomial trees (2018)
  11. Bordes, Laurent; Chauveau, Didier: Stochastic EM algorithms for parametric and semiparametric mixture models for right-censored lifetime data (2016)
  12. González, Miguel; Gutiérrez, Cristina; Martínez, Rodrigo; Minuesa, Carmen; del Puerto, Inés M.: Bayesian analysis for controlled branching processes (2016)
  13. Kustosz, Christoph P.; Leucht, Anne; Müller, Christine H.: Tests based on simplicial depth for AR(1) models with explosion (2016)
  14. Marius Hofert; Martin Mächler: Parallel and Other Simulations in R Made Easy: An End-to-End Study (2016) not zbMATH
  15. Matloff, Norman: Parallel computing for data science. With examples in R, C++ and CUDA (2016)
  16. Teisseyre, Paweł; Kłopotek, Robert A.; Mielniczuk, Jan: Random subspace method for high-dimensional regression with the \textttRpackage \textttregRSM (2016)
  17. Bernd Bischl; Michel Lang; Olaf Mersmann; Jörg Rahnenführer; Claus Weihs: BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments (2015) not zbMATH
  18. Christopher Paciorek; Benjamin Lipshitz; Wei Zhuo; Prabhat; Cari G. Kaufman; Rollin Thomas: Parallelizing Gaussian Process Calculations in R (2015) not zbMATH
  19. Weihs, Claus; Mersmann, Olaf; Ligges, Uwe: Foundations of statistical algorithms. With references to R packages (2014)
  20. Fellinghauer, Bernd; Bühlmann, Peter; Ryffel, Martin; von Rhein, Michael; Reinhardt, Jan D.: Stable graphical model estimation with random forests for discrete, continuous, and mixed variables (2013)

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