EMG                     Single-subject time series of facial
                        electromyography data
EMGsim                  Simulated single-subject time series to capture
                        features of facial electromyography data
LogisticSetPointSDE     Simulated time series data for a stochastic
                        linear damped oscillator model with logistic
                        time-varying setpoints
NonlinearDFAsim         Simulated multi-subject time series based on a
                        dynamic factor analysis model with nonlinear
                        relations at the latent level
Oscillator              Simulated time series data of a damped linear
                        oscillator
Outliers                Simulated time series data for detecting
                        outliers.
PFAsim                  Simulated time series data of a multisubject
                        process factor analysis
PPsim                   Simulated time series data for multiple
                        eco-systems based on a predator-and-prey model
RSPPsim                 Simulated time series data for multiple
                        eco-systems based on a regime-switching
                        predator-and-prey model
autoplot.dynrTaste      The ggplot of the outliers estimates.
coef.dynrModel          Extract fitted parameters from a dynrCook
                        Object
confint.dynrCook        Confidence Intervals for Model Parameters
diag,character-method   Create a diagonal matrix from a character
                        vector
dynr-package            Dynamic Modeling in R
dynr.cook               Cook a dynr model to estimate its free
                        parameters
dynr.data               Create a list of data for parameter estimation
                        (cooking dynr) using 'dynr.cook'
dynr.ggplot             The ggplot of the smoothed state estimates and
                        the most likely regimes
dynr.ldl                LDL Decomposition for Matrices
dynr.mi                 Multiple Imputation of dynrModel objects
dynr.model              Create a dynrModel object for parameter
                        estimation (cooking dynr) using 'dynr.cook'
dynr.plotFreq           Plot of the estimated frequencies of the
                        regimes across all individuals and time points
                        based on their smoothed regime probabilities
dynr.taste              Detect outliers in state space models.
dynr.taste2             Re-fit state-space model using the estimated
                        outliers.
dynr.version            Current Version String
dynrCook-class          The dynrCook Class
dynrDynamics-class      The dynrDynamics Class
dynrInitial-class       The dynrInitial Class
dynrMeasurement-class   The dynrMeasurement Class
dynrModel-class         The dynrModel Class
dynrNoise-class         The dynrNoise Class
dynrRecipe-class        The dynrRecipe Class
dynrRegimes-class       The dynrRegimes Class
dynrTrans-class         The dynrTrans Class
internalModelPrep       Do internal model preparation for dynr
logLik.dynrCook         Extract the log likelihood from a dynrCook
                        Object
names,dynrCook-method   Extract the free parameter names of a dynrCook
                        object
names,dynrModel-method
                        Extract the free parameter names of a dynrModel
                        object
nobs.dynrCook           Extract the number of observations for a
                        dynrCook object
nobs.dynrModel          Extract the number of observations for a
                        dynrModel object
plot.dynrCook           Plot method for dynrCook objects
plotFormula             Plot the formula from a model
prep.formulaDynamics    Recipe function for specifying dynamic
                        functions using formulas
prep.initial            Recipe function for preparing the initial
                        conditions for the model.
prep.loadings           Recipe function to quickly create factor
                        loadings
prep.matrixDynamics     Recipe function for creating Linear Dynamcis
                        using matrices
prep.measurement        Prepare the measurement recipe
prep.noise              Recipe function for specifying the measurement
                        error and process noise covariance structures
prep.regimes            Recipe function for creating regime switching
                        (Markov transition) functions
prep.tfun               Create a dynrTrans object to handle the
                        transformations and inverse transformations of
                        model paramters
printex                 The printex Method
summary.dynrCook        Get the summary of a dynrCook object
vcov.dynrCook           Extract the Variance-Covariance Matrix of a
                        dynrCook object
