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{{{xparam1}}} becomes a structure with the following fields
 * value
{{{xparam1}}} is a column n by 1 vector holding the current values of the estimated parameters (n is the number of parameters).

--({{{xparam1}}} becomes)-- {{{parameters_description}}} is a (global?) strucure array (with n lines) describing the estimated parameters with the following fields:
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 * ID1
 * ID2 (for correlations)
   - 1: standard deviation of a structural shock.
   - 2: standard deviation of a measurement error.
   - 3: correlation betwwen two structural shocks.
   - 4: correlation between two measurement errors.
   - 5: "deep" parameter.
 * ID1 (first exogenous or endogenous variable index for the estimated standard deviation)
 * ID2 (second exogenous or endogenous variable index for the estimated correlations)
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Remark 1. Field ID2 is empty if the corresponding estimated parameter is not a correlation.

Remark 2. Field ID1 is empty if the corresponding estimated parameter is not a correlation or standard deviation.

Remark 3. Period1 and Period2 specify the closed sub sample used to estimate the parameter.

Proposed specification for estimation functions

This includes factorization of common code and extensions for (unexpected) structural change

Estimated parameters description

xparam1 is a column n by 1 vector holding the current values of the estimated parameters (n is the number of parameters).

xparam1 becomes parameters_description is a (global?) strucure array (with n lines) describing the estimated parameters with the following fields:

  • type (1,2,3,4,5)
    • - 1: standard deviation of a structural shock. - 2: standard deviation of a measurement error. - 3: correlation betwwen two structural shocks. - 4: correlation between two measurement errors. - 5: "deep" parameter.
  • ID1 (first exogenous or endogenous variable index for the estimated standard deviation)
  • ID2 (second exogenous or endogenous variable index for the estimated correlations)
  • Period1 (beginning of sub-period)
  • Period2 (end of sub-period)

Remark 1. Field ID2 is empty if the corresponding estimated parameter is not a correlation.

Remark 2. Field ID1 is empty if the corresponding estimated parameter is not a correlation or standard deviation.

Remark 3. Period1 and Period2 specify the closed sub sample used to estimate the parameter.

Functions

  • Likelihood/posterior evaluation (separate two functions ?)
    • - INPUTS: xparam1, data, prior_specifications, ys, coeff_trends, M_.params, M_.Sigma_e, M_.H, list_of_observed_variables - OUTPUTS: likelihood/posterior value, info
    • parameter updates (for period 1):
      • - INPUTS: xparam1, ys, coeff_trends,M_.params, M_.Sigma_e, M_.H - OUTUTS: coeff_trends, params, Sigma_e, H
    • reduced form (for period 1):
      • - INPUTS: params - OUTPUTS: T R ys - computes steady state - computes linear solution for state variables + observed variables
    • data_filtering (for period 1):
      • - INPUTS: data, ys, coeff_trends, Period1, Period2 - OUTPUTS: centered_data for subperiod
    • Kalman filter initialization
      • - INPUTS: Sigma_e T R list_of_observed_variables - OUTPUTS: a0 P0 Z - Remark: Z is computed only for nonstationary models. mfs is computed once before these functions
        • Diffuse Kalman filter recursions takes place here ?
      LOOP on periods 1 to NP:
      • Kalman filter - INPUTS: a0 Po Z T R centered_data Sigma_e H - OUTPUTS: log-likelihood, a(t|t-1), P(t|t-1)

        if period < NP:

        • parameter updates
        • reduced form
        • data_filtering
      END LOOP
    • priors evaluation

DynareWiki: EstimationModule (last edited 2011-07-05 09:43:21 by SébastienVillemot)