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Plotting options

Loading dataset and libraries

library(flexFitR)
library(dplyr)
library(kableExtra)
library(ggpubr)
library(purrr)
data(dt_potato)
head(dt_potato) |> kable()
Trial Plot Row Range gid DAP Canopy GLI
HARS20_chips 1 1 1 W17037-24 0 0.000 0.0000000
HARS20_chips 1 1 1 W17037-24 29 0.000 0.0027216
HARS20_chips 1 1 1 W17037-24 36 0.670 -0.0008966
HARS20_chips 1 1 1 W17037-24 42 15.114 0.0322547
HARS20_chips 1 1 1 W17037-24 56 75.424 0.2326896
HARS20_chips 1 1 1 W17037-24 76 99.811 0.3345619

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")

plot derivatives

# Model coefficients
plot(mod, type = 2, color = "blue", id = plots, label_size = 10)

plot coef

# 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)

plot derivatives

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.