-
Notifications
You must be signed in to change notification settings - Fork 15
/
Copy pathDESCRIPTION
84 lines (84 loc) · 2.72 KB
/
DESCRIPTION
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
Package: ctsem
Type: Package
Title: Continuous Time Structural Equation Modelling
Version: 3.10.2
Date: 2025-1-9
Authors@R: c(person("Charles", "Driver", role =
c("aut","cre","cph"),email="[email protected]"),
person("Manuel", "Voelkle", role = c("aut","cph")),
person("Han", "Oud", role = c("aut","cph") ),
person("Trustees of Columbia University",role='cph'))
Description: Hierarchical continuous (and discrete) time state space modelling, for linear
and nonlinear systems measured by continuous variables, with limited support for
binary data. The subject specific dynamic system is modelled as a stochastic
differential equation (SDE) or difference equation, measurement models are typically multivariate normal factor models.
Linear mixed effects SDE's estimated via maximum likelihood and optimization are the default.
Nonlinearities, (state dependent parameters) and random effects on all parameters
are possible, using either max likelihood / max a posteriori optimization
(with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling.
See <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf>
for details. Priors may be used. For the conceptual overview of the hierarchical Bayesian
linear SDE approach,
see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>.
Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> .
Stan based functions are not available on 32 bit Windows systems at present.
<https://cdriver.netlify.app/> contains some tutorial blog posts.
License: GPL-3
Depends:
R (>= 4.2.0),
Rcpp (>= 0.12.16)
URL: https://github.com/cdriveraus/ctsem
Imports:
cOde,
data.table (>= 1.12.8),
datasets,
Deriv,
expm,
ggplot2,
graphics,
grDevices,
MASS,
Matrix,
methods,
mize,
mvtnorm,
parallel,
plyr,
RcppParallel (>= 5.0.1),
rstan (>= 2.26.0),
rstantools (>= 2.3.0),
stats,
tibble,
tools,
utils,
splines,
statmod
Encoding: UTF-8
LazyData: true
ByteCompile: true
LinkingTo:
BH (>= 1.66.0-1),
Rcpp (>= 0.12.16),
RcppEigen (>= 0.3.3.4.0),
RcppParallel (>= 5.0.1),
rstan (>= 2.26),
StanHeaders (>= 2.26.0),
RcppParallel (>= 5.0.1)
Suggests:
knitr,
testthat,
devtools,
DEoptim,
tinytex,
lme4,
shiny,
gridExtra,
arules,
collapse,
qgam,
papaja
VignetteBuilder: knitr
RoxygenNote: 7.3.2
SystemRequirements: GNU make
NeedsCompilation: yes
Biarch: true