Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----srr, eval = FALSE, echo = FALSE------------------------------------------
# #' @srrstats {G2.0a}
# #' @srrstats {G2.1a}
# #' @srrstats {RE1.1}
## ----setup, message=FALSE-----------------------------------------------------
library(GLMMcosinor)
library(dplyr)
## ----echo=F-------------------------------------------------------------------
withr::with_seed(
50,
{
testdata_simple <- simulate_cosinor(
1000,
n_period = 2,
mesor = 5,
amp = 2,
acro = 1,
beta.mesor = 4,
beta.amp = 1,
beta.acro = 0.5,
family = "poisson",
period = c(12),
n_components = 1,
beta.group = TRUE
)
testdata_simple_gaussian <- simulate_cosinor(
1000,
n_period = 2,
mesor = 5,
amp = 2,
acro = 1,
beta.mesor = 4,
beta.amp = 1,
beta.acro = 0.5,
family = "gaussian",
period = c(12),
n_components = 1,
beta.group = TRUE
)
testdata_two_components <- simulate_cosinor(
1000,
n_period = 10,
mesor = 7,
amp = c(0.1, 0.4),
acro = c(1, 1.5),
beta.mesor = 4.4,
beta.amp = c(2, 1),
beta.acro = c(1, -1.5),
family = "poisson",
period = c(12, 6),
n_components = 2,
beta.group = TRUE
)
}
)
## ----eval = F-----------------------------------------------------------------
# testdata_simple <- simulate_cosinor(
# 1000,
# n_period = 2,
# mesor = 5,
# amp = 2,
# acro = 1,
# beta.mesor = 4,
# beta.amp = 1,
# beta.acro = 0.5,
# family = "poisson",
# period = c(12),
# n_components = 1,
# beta.group = TRUE
# )
## ----message=F, warning=F-----------------------------------------------------
object <- cglmm(
Y ~ amp_acro(times,
period = 12
),
data = filter(testdata_simple, group == 0),
family = poisson()
)
object
## -----------------------------------------------------------------------------
autoplot(object, superimpose.data = TRUE)
## ----eval=F-------------------------------------------------------------------
# testdata_simple_gaussian <- simulate_cosinor(
# 1000,
# n_period = 2,
# mesor = 5,
# amp = 2,
# acro = 1,
# beta.mesor = 4,
# beta.amp = 1,
# beta.acro = 0.5,
# family = "gaussian",
# period = c(12),
# n_components = 1,
# beta.group = TRUE
# )
## ----message=F, warning=F-----------------------------------------------------
object <- cglmm(
Y ~ amp_acro(times,
period = 12,
group = "group"
),
data = testdata_simple_gaussian,
family = gaussian
)
object
## -----------------------------------------------------------------------------
autoplot(object)
## ----message=F, warning=F-----------------------------------------------------
object <- cglmm(
Y ~ group + amp_acro(times,
period = 12,
group = "group"
),
data = testdata_simple_gaussian,
family = gaussian()
)
object
## -----------------------------------------------------------------------------
autoplot(object)
## ----message=F, warning=F-----------------------------------------------------
cglmm(
Y ~ 0 + group + amp_acro(times,
period = 12,
group = "group"
),
data = testdata_simple,
family = poisson()
)
## ----eval=F-------------------------------------------------------------------
# testdata_two_components <- simulate_cosinor(
# 1000,
# n_period = 10,
# mesor = 7,
# amp = c(0.1, 0.4),
# acro = c(1, 1.5),
# beta.mesor = 4.4,
# beta.amp = c(2, 1),
# beta.acro = c(1, -1.5),
# family = "poisson",
# period = c(12, 6),
# n_components = 2,
# beta.group = TRUE
# )
## ----message=F, warning=F-----------------------------------------------------
cglmm(
Y ~ group + amp_acro(
time_col = times,
n_components = 2,
period = c(12, 6),
group = c("group", "group")
),
data = testdata_two_components,
family = poisson()
)
## ----message=F, warning=F-----------------------------------------------------
testdata_disp_zi <- simulate_cosinor(1000,
n_period = 6,
mesor = 7,
amp = c(0.1, 0.4, 0.5),
acro = c(1, 1.5, 0.1),
beta.mesor = 4.4,
beta.amp = c(2, 1, 0.4),
beta.acro = c(1, -1.5, -1),
family = "gaussian",
period = c(12, 6, 8),
n_components = 3
)
object_disp_zi <- cglmm(
Y ~ group + amp_acro(times,
n_components = 3,
period = c(12, 6, 8),
group = "group"
),
data = testdata_disp_zi, family = gaussian(),
dispformula = ~ group + amp_acro(times,
n_components = 2,
group = "group",
period = c(12, 6)
),
ziformula = ~ group + amp_acro(times,
n_components = 3,
group = "group",
period = c(7, 8, 2)
)
)
object_disp_zi
## ----message=F, warning=F-----------------------------------------------------
object <- cglmm(
Y ~ group + amp_acro(times,
period = 12,
group = "group"
),
data = testdata_simple,
family = poisson()
)
summary(object)
## ----message=F, warning=F-----------------------------------------------------
summary(object_disp_zi)
## -----------------------------------------------------------------------------
library(DHARMa)
plotResiduals(simulateResiduals(object$fit))
plotQQunif(simulateResiduals(object$fit))
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