⇤ ← Revision 1 as of 2009-09-17 10:43:03
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Deletions are marked like this. | Additions are marked like this. |
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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 ?
- 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
- - 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
- priors evaluation