MAJOR BUG FIX with smoothed latent state covariance
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
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
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
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
Noise printing by plotFormula() function
Fixed innovation vector computation for larger than 1-dimensional observations
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
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
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.
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.