## Dynamic structural equation
models

Package *dsem* fits dynamic structural equation models, which
includes as nested submodels:

- structural equation models
- vector autoregressive models
- dynamic factor analysis
- state-space autoregressive integrated moving average (ARIMA)
models

The model has several advantages:

- It estimates direct, indirect, and total effects among system
variables, including simultaneous and lagged effects and recursive
(cyclic) dependencies
- It can estimate the cumulative outcome from press or pulse
experiments or initial conditions that differ from the stationary
distribution of system dynamics
- It estimates structural linkages as regression slopes while jointly
imputing missing values and/or measurement errors
- It is rapidly fitted as a Gaussian Markov random field (GMRF) in a
Generalized Linear Mixed Model (GLMM), with speed and asymptotics
associated with each
- It allows granular control over the number of parameters (and
restrictions on parameters) used to structure the covariance among
variables and over time,

*dsem* is specifically intended as a minimal implementation,
and uses standard packages to simplify input/output formatting:

- Input: time-series defined using class
*ts*, with
`NA`

for missing values
- Input: structural trade-offs specified using syntax defined by
package
*sem*
- Output: visualizing estimated trade-offs using
*igraph*
- Output: access model output using standard S3-generic functions
including
`summary`

, `predict`

,
`residuals`

, `simulate`

, and `AIC`

Please see package vignettes for more details regarding syntax and
features.