Different optimization routines & bad bayesian IRFs plot

Hi everybody!
i was doing a DSGE model using bayesian technique. when i set in the “estimation()” with “mode_compute = 4”, i got note:
??? Error using ==> chol
Matrix must be positive definite.

Error in ==> metropolis_hastings_initialization at 52
d = chol(vv);

Error in ==> random_walk_metropolis_hastings at 58
ix2, ilogpo2, ModelName, MhDirectoryName, fblck, fline, npar, nblck, nruns, NewFile, MAX_nruns, d ] = …

while after using optimization routine “mode_compute = 6”, i can get the estimation results, but the Bayesian IFRs are not desirable, most like sharp cliffs or responses in big scale between each plot.

i don’t know what to do next. any help is much appreaciated!


can anyone help me?

If your model and the observation equation is correct, the problem is with finding the mode given your starting values for estimation. This is a general and common problem (lots of posts). One way would be to increase the default parameters of mode_compute=6, see dynare.org/DynareWiki/MonteCarloOptimization