Independence Testing via Hilbert Schmidt Independence Criterion
Contains an implementation of the
d-variable Hilbert Schmidt independence criterion
and several hypothesis tests based on it.

Contains an implementation of the
d-variable Hilbert Schmidt independence criterion
and several hypothesis tests based on it, as described
in Pfister et al. (2017) <doi:10.1111/rssb.12235>.

Time Series Regression Models with Distributed Lag Models
Provides time series regression models with one predictor using finite distributed lag models, polynomial (Almon) distributed lag models, geometric distributed lag models with Koyck transformation, and autoregressive distributed lag models. It also consists of functions for computation of h-step ahead forecasts from these models. See Baltagi (2011) <doi:10.1007/978-3-642-20059-5> for more information.

Haydar Demirhan [aut, cre, cph] (<https://orcid.org/0000-0002-8565-4710>)
stats, dynlm, wavethresh, AER, formula.tools, plyr

AER, formula.tools, plyr , lmtest, strucchange, wavethresh

graphics, stats, nardl, dynlm, R (>= 3.5.0)
AER, formula.tools, plyr , lmtest, strucchange, wavethresh,
MASS, roll

Provides time series regression models with one predictor using finite distributed lag models, polynomial (Almon) distributed lag models, geometric distributed lag models with Koyck transformation, and autoregressive distributed lag models. It also consists of functions for computation of h-step ahead forecasts from these models. See Demirhan (2020)(<doi:10.1371/journal.pone.0228812>) and Baltagi (2011)(<doi:10.1007/978-3-642-20059-5>) for more information.

graphics, stats, nardl, dynlm, R (>= 3.6.0)

AER, formula.tools, plyr , lmtest, strucchange, wavethresh,
MASS, roll, sandwich

Dynamic Modeling and Parameter Estimation in ODE Models
The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.