The numerical treatment of optimal switching problems in a finite time setting when the state evolves as a controlled Markov chain consisting of a uncontrolled continuous component following linear dynamics and a controlled Markov chain taking values in a finite set. The reward functions are assumed to be convex and Lipschitz continuous in the continuous state. The action set is finite.

Visualization of Restricted Cubic Splines
c(
person("Zhiqiang", "Nie",     email = "niezhiqiang@gdph.org.cn", role = c("aut", "cre", "cph"),
comment = c("ORCID = 0000-0001-7642-3286")),
person("JunZhang",        email = "3219030654@stu.cpu.edu.cn", role = "ctb"),
person("Leichao", "Chen",  email = "15626049801@163.com", role = "ctb")
)
Restricted Cubic Splines were performed to explore the shape of association form of "U, inverted U,
L" shape and test linearity or non-linearity base on "Cox,Logistic,linear" regression, and auto output Restricted Cubic Splines figures.
The Restricted Cubic Splines method were based on
Suli Huang (2022) <doi:10.1016/j.ecoenv.2022.113183>,Amit Kaura (2019) <doi:10.1136/bmj.l6055>,
and Harrell Jr (2015, ISBN:978-3-319-19424-0 (Print) 978-3-319-19425-7 (Online)).
pacman, rms, ggplot2, survminer, segmented, survival, dplyr,
patchwork, Cairo
Zhiqiang Nie [aut, cre, cph] (ORCID = 0000-0001-7642-3286),
JunZhang [ctb],
Leichao Chen [ctb]

c(
person("Zhiqiang", "Nie",     email = "niezhiqiang@gdph.org.cn", role = c("aut", "cre", "cph"),
comment = c("ORCID = 0000-0001-7642-3286", "wechat = Biostatistics-SCI")),
person("JunZhang",        email = "3219030654@stu.cpu.edu.cn", role = "ctb"),
person("Chaolei", "Chen",  email = "15626049801@163.com", role = "ctb")
)
Zhiqiang Nie [aut, cre, cph] (ORCID = 0000-0001-7642-3286, wechat =
Biostatistics-SCI),
JunZhang [ctb],
Chaolei Chen [ctb]

Predict Fish Year-Class Strength from Survey Data
c(
person("Colin", "Millar", role = c("aut", "cre"), email="colin.millar@ices.dk"),
person("Marc", "Taylor", role = "aut")
)
Predict fish year-class strength by calibration
regression analysis of multiple recruitment index series.
Colin Millar [aut, cre],
Marc Taylor [aut]