numDeriv

R package numDeriv: Accurate Numerical Derivatives. This package provide methods for calculating (usually) accurate numerical first and second order derivatives. Accurate calculations are done using Richardson’s extrapolation or, when applicable, a complex step derivative is available. A simple difference method is also provided. Simple difference is (usually) less accurate but is much quicker than Richardson’s extrapolation and provides a useful cross-check. Methods are provided for real scalar and vector valued functions.


References in zbMATH (referenced in 51 articles )

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  1. Lisa Amrhein, Christiane Fuchs: stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R (2020) arXiv
  2. Alireza S. Mahani; Mansour T.A. Sharabiani: Bayesian, and Non-Bayesian, Cause-Specific Competing-Risk Analysis for Parametric and Nonparametric Survival Functions: The R Package CFC (2019) not zbMATH
  3. David Ardia; Keven Bluteau; Kris Boudt; Leopoldo Catania; Denis-Alexandre Trottier: Markov-Switching GARCH Models in R: The MSGARCH Package (2019) not zbMATH
  4. David Ardia; Kris Boudt; Leopoldo Catania: Generalized Autoregressive Score Models in R: The GAS Package (2019) not zbMATH
  5. David Smith; Malcolm Faddy: Mean and Variance Modeling of Under-Dispersed and Over-Dispersed Grouped Binary Data (2019) not zbMATH
  6. Di Caterina, Claudia; Kosmidis, Ioannis: Location-adjusted Wald statistics for scalar parameters (2019)
  7. Grün, Bettina; Miljkovic, Tatjana: Extending composite loss models using a general framework of advanced computational tools (2019)
  8. Hirk, Rainer; Hornik, Kurt; Vana, Laura: Multivariate ordinal regression models: an analysis of corporate credit ratings (2019)
  9. Sellers, Kimberly F.; Young, Derek S.: Zero-inflated sum of Conway-Maxwell-poissons (ZISCMP) regression (2019)
  10. Bonat, Wagner Hugo; Lopes, José Evandeilton; Shimakura, Silvia Emiko; Ribeiro, Paulo Justiniano jun.: Likelihood analysis for a class of simplex mixed models (2018)
  11. Gallardo, Diego I.; Gómez, Yolanda M.; de Castro, Mário: A flexible cure rate model based on the polylogarithm distribution (2018)
  12. Hofert, Marius; Kojadinovic, Ivan; Mächler, Martin; Yan, Jun: Elements of copula modeling with R (2018)
  13. John Hughes: sklarsomega: An R Package for Measuring Agreement Using Sklar's Omega Coefficient (2018) arXiv
  14. Kulshreshtha, K.; Narayanan, S. H. K.; Bessac, J.; MacIntyre, K.: Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C (2018)
  15. Salehi, Mahdi; Azzalini, Adelchi: On application of the univariate Kotz distribution and some of its extensions (2018)
  16. Tomaya, Lorena Cáceres; De Castro, Mário: A heteroscedastic measurement error model based on skew and heavy-tailed distributions with known error variances (2018)
  17. Yoshiba, Toshinao: Maximum likelihood estimation of skew-(t) copulas with its applications to stock returns (2018)
  18. Bonat, Wagner Hugo; Kokonendji, Célestin C.: Flexible Tweedie regression models for continuous data (2017)
  19. Bradley Saul; Michael Hudgens: A Recipe for inferference: Start with Causal Inference. Add Interference. Mix Well with R. (2017) not zbMATH
  20. Fernández-Fontelo, Amanda; Fontdecaba, Sara; Alba, Anna; Puig, Pedro: Integer-valued AR processes with Hermite innovations and time-varying parameters: an application to bovine fallen stock surveillance at a local scale (2017)

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