R package rootSolve: Nonlinear root finding, equilibrium and steady-state analysis of ordinary differential equations. Routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE). Includes routines that: (1) generate gradient and Jacobian matrices (full and banded), (2) find roots of non-linear equations by the Newton-Raphson method, (3) estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the Newton-Raphson method, or by dynamically running, (4) solve the steady-state conditions for uni-and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ODEs by numerical differencing (using the method-of-lines approach). Includes fortran code.
Keywords for this software
References in zbMATH (referenced in 9 articles )
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- Howard, James P. II: Computational methods for numerical analysis with R (2017)
- Shakil, M.; Ahsanullah, M.: Some inferences on the distribution of the demmel condition number of complex Wishart matrices (2017)
- Gerhart, Christoph: A multiple-curve Lévy forward rate model in a two-price economy (2016)
- Pantoja-Hernández, Libertad; Álvarez-Buylla, Elena; Aguilar-Ibáñez, Carlos F.; Garay-Arroyo, Adriana; Soria-López, Alberto; Martínez-García, Juan Carlos: Retroactivity effects dependency on the transcription factors binding mechanisms (2016)
- Bloomfield, Victor A.: Using R for numerical analysis in science and engineering (2014)
- Mazzia, Francesca; Cash, Jeff R.; Soetaert, Karline: Solving boundary value problems in the open source software R: package bvpSolve (2014)
- Mazzia, Francesca; Cash, Jeff R.; Soetaert, Karline: A test set for stiff initial value problem solvers in the open source software R: Package \bfdeTestSet (2012)
- Soetaert, Karline; Cash, Jeff; Mazzia, Francesca: Solving differential equations in R. (2012)
- Karline Soetaert; Thomas Petzoldt: Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME (2010)