R package nleqslv: Solve Systems of Nonlinear Equations. Solve a system of nonlinear equations using a Broyden or a Newton method with a choice of global strategies such as line search and trust region. There are options for using a numerical or user supplied Jacobian, for specifying a banded numerical Jacobian and for allowing a singular or ill-conditioned Jacobian.

References in zbMATH (referenced in 22 articles )

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  1. Burch, Brent D.: A family of unbiased confidence intervals for a ratio of variance components (2021)
  2. Gholami, Gholamhossein; Pourdarvish, Ahmad; Mirmostafaee, Seyed Mohammad Taghi; Alizadeh, Morad; Nashi, Ali Najibpour: On the gamma Gumbel distribution (2020)
  3. Joukar, A.; Ramezani, M.; Mirmostafaee, S. M. T. K.: Estimation of (P(X > Y)) for the power Lindley distribution based on progressively type II right censored samples (2020)
  4. Liu, Lan; Miao, Wang; Sun, Baoluo; Robins, James; Tchetgen Tchetgen, Eric: Identification and inference for marginal average treatment effect on the treated with an instrumental variable (2020)
  5. Amrei Stammann, Daniel Czarnowske: Binary Choice Models with High-Dimensional Individual and Time Fixed Effects (2019) arXiv
  6. Laumen, Benjamin; Cramer, Erhard: Progressive censoring with fixed censoring times (2019)
  7. MirMostafaee, S. M. T. K.; Alizadeh, Morad; Altun, Emrah; Nadarajah, Saralees: The exponentiated generalized power Lindley distribution: properties and applications (2019)
  8. Zhang, Qihuang; Yi, Grace Y.: R package for analysis of data with mixed measurement error and misclassification in covariates: augSIMEX (2019)
  9. Zhang, Ru; Lin, C. Devon; Ranjan, Pritam: A sequential design approach for calibrating dynamic computer simulators (2019)
  10. John Monaco; Malka Gorfine; Li Hsu: General Semiparametric Shared Frailty Model: Estimation and Simulation with frailtySurv (2018) not zbMATH
  11. Olmo-Jiménez, María José; Rodríguez-Avi, José; Cueva-López, Valentina: A review of the CTP distribution: a comparison with other over- and underdispersed count data models (2018)
  12. Sun, Ying; Chang, Xiaohui; Guan, Yongtao: Flexible and efficient estimating equations for variogram estimation (2018)
  13. Wentz, J. M.; Mendenhall, A. R.; Bortz, D. M.: Pattern formation in the longevity-related expression of heat shock protein-16.2 in Caenorhabditis elegans (2018)
  14. Bee, M.: Density approximations and VaR computation for compound Poisson-lognormal distributions (2017)
  15. Clarke, Brenton R.; Davidson, Thomas; Hammarstrand, Robert: A comparison of the (L_2) minimum distance estimator and the EM-algorithm when fitting (k)-component univariate normal mixtures (2017)
  16. Shakil, M.; Ahsanullah, M.: Some inferences on the distribution of the Demmel condition number of complex Wishart matrices (2017)
  17. Katahira, Kentaro: How hierarchical models improve point estimates of model parameters at the individual level (2016)
  18. Moliere Nguile-Makao; Alexandre Bureau: Semi-Parametric Maximum Likelihood Method for Interaction in Case-Mother Control-Mother Designs: Package SPmlficmcm (2015) not zbMATH
  19. Chiou, Sy Han; Kang, Sangwook; Yan, Jun: Fast accelerated failure time modeling for case-cohort data (2014)
  20. Nash, John C.: Nonlinear parameter optimization using R tools (2014)

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