## 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.