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    • Fix typos authored by Sébastien Villemot's avatar Sébastien Villemot
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    NewFeatures.md
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    ......@@ -4,7 +4,7 @@ the [DynareWiki](http://www.dynare.org/DynareWiki/NewFeatures).
    Dynare 4.7 (unstable)
    ---------------------
    - New Method of Moments toolbox: `method_of_moments` command (Dynare/dynare!1750) and `matched_moments` block (Dynare/preprocessor!23) that provide functionality to estimate parameters by (i) Generalized Method of Moments (GMM up to 3rd-order pruned perturbation approximation or (ii) Simulated Method of Moments (SMM) up to any perturbation approximation order. Toolbox is inspired by replication codes accompanied to Andreasen et al. (2018), Born and Pfeifer (2014), and Mutschler (2018).
    - New Method of Moments toolbox: `method_of_moments` command (Dynare/dynare!1750) and `matched_moments` block (Dynare/preprocessor!23) that provide functionality to estimate parameters by (i) Generalized Method of Moments (GMM) up to 3rd-order pruned perturbation approximation or (ii) Simulated Method of Moments (SMM) up to any perturbation approximation order. Toolbox is inspired by replication codes accompanied to Andreasen et al. (2018), Born and Pfeifer (2014), and Mutschler (2018).
    - performance optimization to pruned state space system and lyapunov solvers (Dynare/dynare!1749, Dynare/dynare!1745, Dynare/dynare#1737)
    ......@@ -36,7 +36,7 @@ Dynare 4.7 (unstable)
    - the `use_dll` option can now directly be given to the `dynare` command (a9fea692e9d1f4bcdd6a7347a9d17a8b36578a4a)
    - when compiling from source, it is no longer to pass the `MATLAB_VERSION` version to the configure script; the version is now automatically detected
    - when compiling from source, it is no longer necessary to pass the `MATLAB_VERSION` version to the configure script; the version is now automatically detected
    - In deterministic models, exogenous variables with lead/lags are now replaced by auxiliary variables. This brings those models in line with the transformation done on stochastic models. However note that transformation is still not exactly the same between the two classes of models, because there is no need to take into account the Jensen inequality on the latter. In deterministic models, there is a one-to-one mapping between exogenous with lead/lags and auxiliaries, while in stochastic models, an auxiliary endo may correspond to a more complex nonlinear expression (preprocessor@9bca65c7e525a2415fe46b27e8760208b22aba9d)
    ......