dynr-package

dynr


\Sexpr[results=rd,stage=build]{tools:::Rd_package_description("#1")}dynrDynamic modeling of all kinds in R. These include models of
    processes in discrete time or continuous time. They also include processes
    that are linear or nonlinear. Latent variables can be continuous (e.g. state
    space models) or discrete (e.g. regime-switching models). The general approach
    involves maximum likelihood estimation of single- and multi-subject models of
    latent time series with the extended Kalman filter and Kim filter. The user
    provides recipes and data which are combined into a model that is then cooked to
    obtain free parameter estimates.<p></p><p></p>

 package

Dynamic modeling of all kinds in R. These include models of
processes in discrete time or continuous time. They also include processes
that are linear or nonlinear. Latent variables can be continuous (e.g. state
space models) or discrete (e.g. regime-switching models). The general approach
involves maximum likelihood estimation of single- and multi-subject models of
latent time series with the extended Kalman filter and Kim filter. The user
provides recipes and data which are combined into a model that is then cooked to
obtain free parameter estimates.

Lu Ou

Dynamic Modeling in R

dynr-package function


\Sexpr[results=rd,stage=build]{tools:::Rd_package_description("#1")}dynrDynamic modeling of all kinds in R. These include models of
    processes in discrete time or continuous time. They also include processes
    that are linear or nonlinear. Latent variables can be continuous (e.g. state
    space models) or discrete (e.g. regime-switching models). The general approach
    involves maximum likelihood estimation of single- and multi-subject models of
    latent time series with the extended Kalman filter and Kim filter. The user
    provides recipes and data which are combined into a model that is then cooked to
    obtain free parameter estimates.



dynr-package: \Sexpr[results=rd,stage=build]{tools:::Rd_package_title("#1")}dynrDynamic Modeling in R

Description

Arguments

Details

References

See Also

Examples