Presents a statistical method that uses a recursive algorithm for signal extraction. The method handles a non-parametric estimation for the correlation of the errors. See "Krivobokova", "Serra", "Rosales" and "Klockmann" (2021) <arXiv:1812.06948> for details.

Presents a statistical method that uses a recursive algorithm for signal extraction. The method handles a non-parametric estimation for the correlation of the errors. For details on the methods see: Serra et al. (2018) <arXiv:1812.06948>.

c(
person(given = "Garritt", family = "L. Page", email = "page@stat.byu.edu", role = c("aut", "cre")),
person(given = "Massimo", family = "Ventrucci", email = "massimo.ventrucci@unibo.it", role = c("aut")),
person(given = "S. McKay", family = "Curtis", email = "s.mckay.curtis@gmail.com", role = c("cph")),
person(given = "Radford", family = "M. Neal", role = c("cph")))
Fits Leroux model in spectral domain to estimate causal spatial effect as detailed in
Guan, Y; Page, G.L.; Reich, B.J.; Ventrucci, M.; Yang, S; (2020) <arXiv:2012.11767>.
Both the parametric and semi-parametric models are available.  The semi-parametric model
relies on 'INLA'.  The 'INLA' package can be obtained from <https://www.r-inla.org/>.
Garritt L. Page [aut, cre],
Massimo Ventrucci [aut],
S. McKay Curtis [cph],
Radford M. Neal [cph]

Simulates cyclic voltammetry, linear-sweep voltammetry
(both with and without stirring of the solution), and single-pulse
and double-pulse chronoamperometry and chronocoulometry
experiments using the implicit finite difference method outlined in
Gosser (1993, ISBN: 9781560810261) and in Brown (2015)
<doi:10.1021/acs.jchemed.5b00225>. Additional functions provide
ways to display and to examine the results of these simulations.
The primary purpose of this package is to provide tools for
use in courses in analytical chemistry.

Dynamic Model Averaging with Grid Search
Perform Dynamic Model Averaging with grid search as in Dangl and Halling (2012) <doi:10.1016/j.jfineco.2012.06.005> using parallel computing.