Dynamic Stochastic General Equilibrium Models R package dsge version 1.0.0 Specify, solve, and estimate dynamic stochastic general equilibrium (DSGE) models by maximum likelihood and Bayesian methods. Supports both linear models via an equation-based formula interface and nonlinear models via string-based equations with first-order perturbation (linearization around deterministic steady state). Solution uses the method of undetermined coefficients (Klein, 2000 <doi:10.1016/S0165-1889(99)00045-7>). Likelihood evaluated via the Kalman filter. Bayesian estimation uses adaptive Random-Walk Metropolis-Hastings with prior specification. Additional tools include Kalman smoothing, historical shock decomposition, local identification diagnostics, parameter sensitivity analysis, second-order perturbation, occasionally binding constraints, impulse-response functions, forecasting, and robust standard errors. Software Depends: R (>= 3.5.0) Imports: grDevices, graphics, stats, numDeriv Suggests: coda, testthat (>= 3.0.0), knitr, rmarkdown Mustapha Wasseja Mohammed <muswaseja@gmail.com> Comprehensive R Archive Network (CRAN) Mustapha Wasseja Mohammed [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=dsge/LICENSE) 2026-04-02 application/tgz https://CRAN.R-project.org/package=dsge doi:10.32614/CRAN.package.dsge