- GetVarRf for FIML,CFIML when there are no estimated parameters returned
*JJ'*instead of*J&*lt;>*J'*(which cannot be computed). Now it returns a matrix of zeros of the same dimension as*JJ'*, so that forecasts with and without parameter uncertainty are the same. (NRE) - Autometrics 1.5g: using standard instead of default for 0.05 in output Using Renew instead of Append in DummySaturation
- Small change in handling of lagged Y's that are classified as U_VAR: now only transforming back to Y_VAR after Autometrics run. Otherwise we get different results when using the PcGive class for estimation only with Autometrics.
- Autometrics block search now works with components (always adding all components into the model)

- Autometrics related:
- Autometrics default now set to 0.01 instead of 0.05
- Added SIS, IIS+SIS, DIIS, DIIS+IIS dummy saturation
- Now have PcGive batch command
`createinterventions`and Ox function`PcGive::CreateInterventions`to construct intervention dummies from saturation in the database. - reclassification of lagged dependent variables from X,U to Y,I is now done at a later stage. This allows forcing of lagged dependent variables when running Autometrics on a system (OLS) or single equation (OLS, IVE)
- additional instruments for IVE (denoted with an A) now is different from unrestricted (U). U is used for unrestricted: not to be removed by automatic model selection.
- removed variables from an IVE model are only made into additional instruments if reduction of the reduced form was used first (which is the default).
- Writing initial GUM when entering k>T.

- Much extended dynamic forecasting:
- Automatic detection of certain types of transformations of the dependent variable Y:

fn(Y), Dfn(Y), DDfn(Y), DD_sfn(Y), D_sfn(y)

where fn(Y): Y, log(Y), logit(Y)

also detects on rhs corresponding fn(Y), Dfn(Y), D_sfn(y) - Based on this a levels forecast will be available in two forms:
- median forcasts: inverse transformation (exp(y), logistic(y))
- mean forecasts: based on lognormal and logitnormal distribution.

- Robust forecasts. Robust forecast are derived from using the model on the differenced data, which is then reintegrated.
- Optionally, forecasting can start a specified number of observations after the end of the estimation sample.
- Hedgehog graphs: forecasts starting from each observation in the estimation sample:
- fixed parameters: the same parameters are used for each forecast
- recursive parameters: if the model is estimated recursively, the recursive parameter estimates are used. So the model is re-estimated each time for the new forecasts.

- Estimating an empty model now does not give an error message anymore, facilitating DDD
- Add documentation to header files, DoForecasting doesn't store SEs, nor are there functions to extract forecasts.

- Automatic detection of certain types of transformations of the dependent variable Y:
- Added X12-ARIMA
- Markov-switching models:
- MS_Component: Markov-switching with component structure for mean and variance
- MS_GARCH: Markov-switching GARCH
- MS_MV: Multifractal volatility models
- MS_VAR: Multivariate Markov switching
- Refactored code to implement improvements in structure.
- Removed singularity in analytical derivatives when probability is (very close to) zero.
- Changed starting values for transition probabilities.
- Probability mask: avoid diagonal when setting 1-sum element
- Ability to set lower pound for probability of staying in same regime (if this is zero, we have identified an outlier - this can be on the boundary of the parameter space with a lower log-likelihood than the interior solution. Default minimum for diagonal of transition matrix (prob of staying) is 0.01.
- reporting sdev(y) not var(y)
- updated NBER info
- Forecasts: not reporting naive forecasts anymore
- Forecast se: only simulating for dynamic models
- Impulse responses with standard errors

- exit batch command crashes OxMetrics
- fixed infinite reload loop in when loading help in Chrome
- CFIML: not forcing rows/columns of restricted parameters to zero anymore in VarCovar matrix. (fixes problem with forecast se when parameter uncertainty is included).
- IVE withholding forecast, store fitted in database gave concatenation warning (but worked fine)
- recursive IVE: default no inits was zero, which didn't work for IVE
- CFIML then FIML: was still estimating CFIML.
- Dummy saturation (IIS) would go haywire if a dummy is already in the model

This file last changed .