results in unit tests (use logical type).

This routine is used to compare objects i -n unit tests.

For m-unit-tests module.

Clarify message in test_for_deep_parameters_calibration.m

Provide example for xls_range option in manual

Add missing run index to looped variable in resol.m

Ramsey aux vars

even if there is a single shock. In that case variance decomposition
is one. It is better if Gamma_y has always the expected
size. disp_th_moments.m only displays variance decomposition if there
is more than one shock.

moments for a model with a single exogenous variable

TBD: add check for correctness. As variables are dummy variables, the solution should be identical to the one without these auxiliary variables

Fix distinction between initial values provided to dyn_ramsey_static.m and stale unchanged initial values in oo_.steady_state

In case of no steady state file, they are identical, but with a steady state file, they are not. Moreover, this fixes a problem with the dimension of the input to the steady state file. ys was not initialized and had wrong dimensions
Also adds comments to file.

Fixed bug (appearing only with Matlab and legacy data interface) if the m data file is in the current directory.

If the m data file is in the current directory, the first output of
fileparts(options_.datafile) is an empty string. In Matlab the command
cd('') fails, but Octave does not fail in this case (and does nothing).

Added a test on the first output of fileparts, if this output is empty
we do not try to change the current directory.

Dataset factorization. Removed tests/kalman/lyapunov/fsdat_simul.m and use tests/fs2000/fsdat_simul.m instead.

An m file data was not loading if outside the current directory.

Note that  all the variables  listed in varobs  need to have  the same
number of observations.

 * Second  and  third  positional  arguments  after the  name  of  the
   estimated  parameter   in  the  estimated_params   block  are  only
   considered in the optimization stage (not in the MCMC)

 * Do not  store bounds  in bayestopt_, because  bounds do  not always
   reflect restrictions implied by prior shapes.

 * prior_bounds routine  returns a structure  (with fields lb  and ub)
   instead of a matrix.

parameters  used   for  optimization  (second   and  third  positional
arguments  after   the  name  of   the  estimated  parameter   in  the
estimated_params block).