Fix crash of perfect foresight w/ expectation errors + marginal linearization + several learnt_in blocks

Fix marginal linearization in the context of perfect_foresight_with_expectation_errors_solver with homotopy

If a solution corresponding to 100% of the shock can’t be found in the first
informational period, marginal linearization will be performed to extrapolate a
solution.

However, in subsequent informational periods, this extrapolated solution cannot
be used for the initial conditions of endogenous variables, because the initial
conditions are not a true solution of the nonlinear model. For those subsequent
informational periods, the correct approach is to compute the two solutions
needed for marginal linearization using as initial conditions the values
obtained in the same two solutions for the previous informational
periods (stored as oo_.deterministic_simulation.{sim1,sim2}).

– new option “endval_steady” to pf_setup command to recompute terminal
  steady state in the homotopy loop

– new options “homotopy_linearization_fallback” and
  “homotopy_marginal_linearization_fallback” to pf_solver and pfwee_solver
  commands, to get an approximate solution when homotopy fails to go to 100%

– new options “homotopy_initial_step_size”, “homotopy_min_step_size”,
  “homotopy_step_size_increase_success_count” and “homotopy_max_completion_share”
  to pf_solver and pfwee_solver commands to fine tune the homotopy behaviour

– removed option “homotopy_alt_starting_point” to pf_solver command, not really
  useful

– new options “steady_solve_algo”, “steady_tolf”, “steady_tolx”,
  “steady_maxit”, “steady_markowitz” to pf_solver and pfwee_solver commands, to
  control the computation of the terminal steady state (and remove the
  equivalent options which previously had different names in pfwee_solver command)