Correct a bug when the model contains deterministic exogenous variables and bytecode option is used.
Note that stochastic simulations do not work for the moment with block option.

put *_params_derivs.m and identification code in conformity with additional steady state argument in *_dynamics.m

new correction for steady_state operator bug. Steady_state vector is passed as argument to *_dynamic model function. As a result, bytecode is currently broken.

The derivatives with respect to endogenous variables of the previous blocks are corrected for a block-decomposed model without bytecode option

- Adds a "lead_lag_incidence" matrix in each block for the endogenous variables belonging to previous blocks (other_endo)

fixed bug: end _dynamic and _static and getPowerDeriv functions with "end" tags to comply with commit d8dbc68e

Bugfix at order 3 (hopefully was not affecting final results, thanks to Pablo Winant for spotting this):
- in the 3rd derivatives matrix, among symmetric elements, the first one had
the right values but the following ones were set to zero
- moreover, the k-order DLL was trying to add all the symmetric elements in the
folded tensor, instead of only keeping one value among all the symmetric ones
- hopefully, Ondra's tensor library was (silently) refusing to add symmetric
elements after the first (and right) value had been added
- so the final result was correct

and corrects the computation of the number of column in the jacobian matrices in a block decomposed model without bytecode
- Identical corrections for models using bytecode without block decomposition

Preprocessor: max lead/lags in the model are no longer affected by lead/lags on parameters (closes #153)

- Add wrapper needed to compute the steady-state using bytecode and solve_algo = 0, ..., 4

in unused model local variables

options (closes #98)

- Changing the the stack_solve_algo option :
Previous version             New version
1 : Sparse LU                0 : Sparse LU
2 : GMRES                    1 : Relaxation
3 : BiCGStab                 2 : GMRES
4 : Sparse LU & Optimal Path 3 : BiCGStab
5 : bytecode own solver      4 : Sparse LU & Optimal Path
                             5 : bytecode own solver

- Substitutes lead for exogenous and endogenous variables in the deterministic case: direct substitution of the variables even in non-linear expressions

Bug correction in the deterministic simulation: to solve a purely backward or forward looking block requires contemporaneous derivatives only.

- preprocessor provides informations about the dynamic structure of each block
- extends the algorithms available with bytecode: stack_solve_algo = 1, 2, 3 and 4 is compatible the bytecode. Speed and memory requirement are improved with stack_solve_algo = 1 or 4 for large scale models.
- bytecode can be used to evaluate a model

redundant with data members, added const keywords, use passing-by-reference)

- remove useless output type oMatlabDynamicModelSparseLocalTemporaryTerms
(indistinguishable from oMatlabDynamicModelSparseLocal)
- fix bug in output type of sparse static model

Preprocessor: in the parameter derivatives file, add the global "oo_" when the STEADY_STATE operator is used

Preprocessor: use a sparse representation for the 2nd derivatives of residual and jacobian w.r.t. parameters and the derivative of hessian w.r.t. parameters

Preprocessor: only compute on demand the 2nd derivatives of residual and jacobian w.r.t. parameters and the derivative of hessian w.r.t. parameters