# What's problem of Subscripted assignment dimension mismatch **URL:** \ **Category:** Dynare help (legacy posts)\ **Created:** [21 November 2010 08:45 UTC](https://forum.dynare.org/t/whats-problem-of-subscripted-assignment-dimension-mismatch/1749 "2010-11-21T08:45:48Z")\ **Posts on this page:** 1\ **Page:** 1
**Author:** ![blackeif](https://forum.dynare.org/letter_avatar_proxy/v4/letter/b/3be4f8/32.png) [@blackeif](https://forum.dynare.org/u/blackeif)\ **Post date:** [21 November 2010 08:45 UTC](https://forum.dynare.org/t/whats-problem-of-subscripted-assignment-dimension-mismatch/1749/1 "2010-11-21T08:45:48Z")
i modefied the linear system for bayesian estimation,the result can estimate the parameters,but also shows erro message as follows,could someone help me with this problem? ans is it necessary to write variables’ steady state value when i use linear system for bayesian estimation?(the mod file and data.m are attached below,it will take about one hours for estimation) ---------------------------------------------------------matlab result------------------------------------------------------------------------------- To get started, select MATLAB Help or Demos from the Help menu. > > dynare exrbyes > > The element type “name” must be terminated by the matching end-tag “”. > > Could not parse the file: c:\matlab7\toolbox\ccslink\ccslink\info.xml Configuring Dynare … [mex] Generalized QZ. [mex] Sylvester equation solution. [mex] Kronecker products. [mex] Sparse kronecker products. [mex] Bytecode evaluation. [mex] k-order perturbation solver. [mex] k-order solution simulation. Starting Dynare (version 4.1.2). Starting preprocessing of the model file … Found 15 equation(s). Evaluating expressions…done Computing static model derivatives: - order 1 Computing dynamic model derivatives: - order 1 - order 2 Processing outputs …done Preprocessing completed. Starting MATLAB/Octave computing. Loading 59 observations from data.m Initial value of the log posterior (or likelihood): -86478379.1768 # ========================================================== Change in the covariance matrix = 9.9996. Mode improvement = 86477751.3739 New value of jscale = 0.0045837 Change in the covariance matrix = 0.12271. Mode improvement = 41.0807 RESULTS FROM POSTERIOR MAXIMIZATION parameters prior mean mode s.d. t-stat prior pstdev bpai 1.500 1.2764 0.0550 23.1874 gamm 0.5000 by 0.500 1.3809 0.0775 17.8245 gamm 0.2000 rho 0.800 0.7671 0.0205 37.4001 beta 0.2000 rhoystar 0.800 1.0000 0.0037 272.8955 beta 0.2000 rhopaistar 0.800 0.7514 0.0223 33.6287 beta 0.2000 rhoistar 0.800 0.8555 0.0254 33.6212 beta 0.2000 bystar 0.500 0.6057 0.0303 19.9833 gamm 0.2000 bpaistar 1.500 2.0717 0.1067 19.4246 gamm 0.5000 taopai 0.800 0.9950 0.0046 216.0475 beta 0.2000 taoy 0.800 0.8524 0.0263 32.4419 beta 0.2000 taoi 0.800 0.6443 0.0305 21.1405 beta 0.2000 gammam 0.500 0.2795 0.0310 9.0288 gamm 0.2000 a1 0.080 0.1126 0.0024 47.7652 gamm 0.0200 a2 0.010 0.0113 0.0003 33.8159 gamm 0.0050 bystar 0.400 0.0442 0.0135 3.2781 gamm 0.2000 bpaistar 0.100 0.0065 0.0034 1.9031 gamm 0.2000 standard deviation of shocks prior mean mode s.d. t-stat prior pstdev uystar 0.010 5.9792 0.3683 16.2324 invg Inf uistar 0.010 0.4683 0.0437 10.7223 invg Inf upaistar 0.010 0.7807 0.0641 12.1738 invg Inf upai 0.010 0.0479 0.0142 3.3642 invg Inf uy 0.010 1.6634 0.3095 5.3748 invg Inf ui 0.010 0.5719 0.0599 9.5458 invg Inf Log data density [Laplace approximation] is -664.977551. MH: Multiple chains mode. MH: Old \_mh files successfully erased! MH: Old metropolis.log file successfully erased! MH: Creation of a new metropolis.log file. MH: Searching for initial values… MH: Initial values found! MH: Old mh\_history file successfully erased! MH: Number of mh files : 4 per block. MH: Total number of generated files : 8. MH: Total number of iterations : 20000. MH: average acceptation rate per chain : 0.4213 0.2649 MH: Total number of Mh draws: 20000. MH: Total number of generated Mh files: 4. MH: I’ll use mh-files 2 to 4. MH: In mh-file number 2 i’ll start at line 4791. MH: Finally I keep 10000 draws. MH: I’m computing the posterior mean and covariance… Done! MH: I’m computing the posterior log marginale density (modified harmonic mean)… MH: Modified harmonic mean estimator, done! ESTIMATION RESULTS Log data density is -672.960240. parameters prior mean post. mean conf. interval prior pstdev bpai 1.500 1.2924 1.2312 1.3669 gamm 0.5000 by 0.500 1.4766 1.3966 1.5716 gamm 0.2000 rho 0.800 0.7903 0.7604 0.8180 beta 0.2000 rhoystar 0.800 0.9987 0.9962 1.0000 beta 0.2000 rhopaistar 0.800 0.7360 0.7007 0.7639 beta 0.2000 rhoistar 0.800 0.8891 0.8549 0.9232 beta 0.2000 bystar 0.500 0.5532 0.4733 0.6599 gamm 0.2000 bpaistar 1.500 1.9231 1.7223 2.1458 gamm 0.5000 taopai 0.800 0.9960 0.9933 0.9997 beta 0.2000 taoy 0.800 0.8403 0.8019 0.8801 beta 0.2000 taoi 0.800 0.6262 0.5599 0.6887 beta 0.2000 gammam 0.500 0.2758 0.2293 0.3459 gamm 0.2000 a1 0.080 0.1110 0.1037 0.1178 gamm 0.0200 a2 0.010 0.0112 0.0108 0.0116 gamm 0.0050 bystar 0.400 0.0586 0.0280 0.0853 gamm 0.2000 bpaistar 0.100 0.0091 0.0046 0.0139 gamm 0.2000 standard deviation of shocks prior mean post. mean conf. interval prior pstdev uystar 0.010 5.1583 4.1687 6.1078 invg Inf uistar 0.010 0.4750 0.4207 0.5454 invg Inf upaistar 0.010 0.8622 0.7433 0.9425 invg Inf upai 0.010 0.0446 0.0340 0.0550 invg Inf uy 0.010 1.7347 1.2911 2.2272 invg Inf ui 0.010 0.5445 0.4514 0.6587 invg Inf ??? Error using ==\> eval Subscripted assignment dimension mismatch. Error in ==\> PlotPosteriorDistributions at 132 eval(‘oo\_.prior\_density.parameters.’ name ‘(:,1) = x2;’]) Error in ==\> dynare\_estimation\_1 at 1075 oo\_ = PlotPosteriorDistributions(estim\_params\_, M\_, options\_, bayestopt\_, oo\_); Error in ==\> dynare\_estimation at 62 dynare\_estimation\_1(var\_list,varargin{:}); Error in ==\> exrbyes at 255 dynare\_estimation(var\_list\_); Error in ==\> dynare at 132 evalin(‘base’,fname) ; > > [data.m](https://forum.dynare.org/uploads/default/original/1X/b7bb8080e05e07affafea2f38c2003d3e8afb108.m) (3.79 KB) [exrbyes.mod](https://forum.dynare.org/uploads/default/original/1X/49047648704453cded00cc5ccb31af6590c1bc5f.mod) (2.67 KB)