This function performs regression analysis using the Hill model.
hill(
trat,
resp,
sample.curve = 1000,
error = "SE",
ylab = "Dependent",
xlab = "Independent",
theme = theme_classic(),
legend.position = "top",
point = "all",
width.bar = NA,
r2 = "all",
textsize = 12,
pointsize = 4.5,
linesize = 0.8,
linetype = 1,
pointshape = 21,
fillshape = "gray",
colorline = "black",
round = NA,
xname.formula = "x",
yname.formula = "y",
comment = NA,
fontfamily = "sans"
)
The function returns a list containing the coefficients and their respective values of p; statistical parameters such as AIC, BIC, pseudo-R2, RMSE (root mean square error); largest and smallest estimated value and the graph using ggplot2 with the equation automatically.
Numeric vector with dependent variable.
Numeric vector with independent variable.
Provide the number of observations to simulate curvature (default is 1000)
Error bar (It can be SE - default, SD or FALSE)
Variable response name (Accepts the expression() function)
treatments name (Accepts the expression() function)
ggplot2 theme (default is theme_bw())
legend position (default is "top")
defines whether you want to plot all points ("all") or only the mean ("mean")
Bar width
coefficient of determination of the mean or all values (default is all)
Font size
shape size
line size
line type
format point (default is 21)
Fill shape
Color lines
round equation
Name of x in the equation
Name of y in the equation
Add text after equation
Font family
Model imported from the aomisc package (Onofri, 2020)
Gabriel Danilo Shimizu
The Hill model is defined by: $$y = \frac{a \times x^c}{b+x^c}$$
Seber, G. A. F. and Wild, C. J (1989) Nonlinear Regression, New York: Wiley & Sons (p. 330).
Onofri A. (2020) The broken bridge between biologists and statisticians: a blog and R package, Statforbiology, IT, web: https://www.statforbiology.com
data("granada")
attach(granada)
hill(time,WL)
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