dynr 0.1.16-XX
- 2021-04-12
 
- MAJOR BUG FIX with smoothed latent state covariance
 
dynr 0.1.15-1
- 2019-10-04
 
- Multiple imputation for missing data with dynr.mi() function
 
- New demo for multiple imputation called MILinearDiscrete
 
- New demo for time-varying parameters called SDETVP
 
- New wrapper functions for computing smoothed derivative estimates
using penalized B-splines implemented with the fda package
 
- New plotting functions, including functions to generate diagnostic
plots from smoothed derivative estimates, and plot phase portraits
 
- New demo for computing and visualizing smoothed derivative estimates
in GetDerivs
 
- New functionality in dynr.cook() to estimate continuous-time dynamic
models with mixed effects through use of theta.formula
 
- MAJOR BUG FIXES with missing data
 
dynr 0.1.14-9
- 2019-04-01
 
- Outlier detection with dynr.taste() function
 
- Oulier removal and re-fitting with dynr.tast2() function
 
- New demo for outliers called OutlierDetection
 
- We now allow 1-regime recipe parts to co-exist with n-regime
parts
 
- Lots of error checking was added around matching the number of
regimes
 
- Many cases of the doDykstra error are now safely caught
 
- Generally cleaned up the error handling on models that failed to
converge
 
- Shorten several demos to run faster
 
dynr 0.1.13-4
- 2018-09-21
 
- You don’t need to install R on Windows to C:/R anymore! The default
(C:/Program Files/R) now works.
 
- New demo for time-varying parameter (TVP) models
 
- Several new vignettes covering a range of topics
 
- The deviation form of regimes now displays properly in
plotFormula
 
- No longer require ‘outfile’ specification in dynr.model()
 
- Fix a pointer addressing issue that could have caused crashes
 
dynr 0.1.12-5
- 2018-02-08
 
- New ‘verbose’ argument to dynr.cook turns off printing of
optimization history
 
- New demo for Process Factor Analysis (PFA)
 
- Regime-switching printing in plotFormula() with new ‘printRS’
argument
 
- Greatly improved convergence rates for all models
 
- Allow full initial covariance estimation
 
- Fixed major bug in regime-switching matrix dynamics that formerly
crashed R
 
dynr 0.1.11-8
- 2017-08-21
 
- Noise printing by plotFormula() function
 
- Fixed innovation vector computation for larger than 1-dimensional
observations
 
dynr 0.1.11-2
- 2017-06-16
 
- New demo for a linear oscillator with time-varying parameters
 
- Fixed printex output for covariates and deviation form of the
initial conditions
 
- Fixed memory leak for intercepts in measurement models
 
dynr 0.1.10
- 2017-05-19
 
- Use of individual-level covariates in the initial conditions. See
?prep.initial for details.
 
- Deviation form of regime-switching models. Seee ?prep.regimes for
details.
 
- Access to the predicted, filtered, and smoothed latent variable
estimates, and other by-products from the regime-switching extended
Kalman filter in the ‘cooked’ model.
 
- We now allow calculation of the negative log-likelihood value, the
hessian matrix, and the predicted, filtered, and smoothed latent
variable estimates at fixed parameter values without parameter
optimization.
 
- Beta version of a multiple imputation procedure. See ?dynr.mi for
details.
 
- Fixed a rounding bug that improves free parameter optimization,
especially for models with many observed variables.
 
- Improved documentation throughout
 
- Added more examples in the help pages
 
dynr 0.1.9
- 2017-02-21
 
- A new demo example is added to replicate the results from Yang &
Chow (2010) paper.
 
- Some standard S3 methods are added for the dynrCook class
object.
 
- autoplot() is added as an alias for dynr.ggplot().
 
- dynr.data() now automatically handles ts class objects and equally
spaced data with missingness.
 
- Changes are made to accommodate the new release of ggplot2.
 
dynr 0.1.8
- 2016-08-12
 
- In single-regime models, free parameters for intercepts and
covariate effects in the measurement model can now be properly
estimated.
 
- Standard errors are more frequently returned
 
- Flags indicate problematic standard errors.
 
- Warning messages are more helpful regarding standard errors.
 
- A weight flag allows easier convergence of multi-subject
models.
 
- Several new plotting features.
 
dynr 0.1.7
- 2016-06-07
 
- Initial release to CRAN!