Modeling
plots <- 2:7
mod <- dt_potato |>
modeler(
x = DAP,
y = Canopy,
grp = Plot,
fn = "fn_logistic",
parameters = c(L = 100, k = 4, t0 = 40),
subset = plots
)
Plotting predictions and derivatives
# Raw data with fitted curves
plot(mod, type = 1, color = "blue", id = plots, title = "Fitted curves")
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# Model coefficients
plot(mod, type = 2, color = "blue", id = plots, label_size = 10)
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# Fitted curves only
c <- plot(mod, type = 3, color = "blue", id = plots, title = "Fitted curves")
# Fitted curves with confidence intervals
d <- plot(
x = mod,
type = 4,
n_points = 200,
color = "black",
title = "Fitted curve (uid = 2)"
)
# First derivative with confidence intervals
e <- plot(
x = mod,
type = 5,
n_points = 200,
color = "black",
title = "1st Derivative (uid = 2)"
)
# Second derivative with confidence intervals
f <- plot(
x = mod,
type = 6,
n_points = 200,
color = "black",
title = "2nd Derivative (uid = 2)"
)
ggarrange(c, d, e, f)
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