logistic {AgroR} | R Documentation |
Logistic regression is a very popular analysis in agrarian sciences, such as in fruit growth curves, seed germination, etc...The logistic function performs the analysis using 3 or 4 parameters of the logistic model, being imported from the LL function .3 or LL.4 of the drc package (Ritz & Ritz, 2016).
logistic(
trat,
resp,
npar = "LL.3",
error = "SE",
ylab = "Dependent",
xlab = expression("Independent"),
theme = theme_classic(),
legend.position = "top",
r2 = "all",
width.bar = NA,
scale = "none",
textsize = 12,
font.family = "sans"
)
trat |
Numerical or complex vector with treatments |
resp |
Numerical vector containing the response of the experiment. |
npar |
Number of model parameters |
error |
Error bar (It can be SE - default, SD or FALSE) |
ylab |
Variable response name (Accepts the expression() function) |
xlab |
Treatments name (Accepts the expression() function) |
theme |
ggplot2 theme (default is theme_bw()) |
legend.position |
Legend position (default is c(0.3,0.8)) |
r2 |
Coefficient of determination of the mean or all values (default is all) |
width.bar |
Bar width |
scale |
Sets x scale (default is none, can be "log") |
textsize |
Font size |
font.family |
Font family (default is sans) |
The three-parameter log-logistic function with lower limit 0 is
f(x) = 0 + \frac{d}{1+\exp(b(\log(x)-\log(e)))}
The four-parameter log-logistic function is given by the expression
f(x) = c + \frac{d-c}{1+\exp(b(\log(x)-\log(e)))}
The function is symmetric about the inflection point (e).
The function allows the automatic graph and equation construction of the logistic model, provides important statistics, such as the Akaike (AIC) and Bayesian (BIC) inference criteria, coefficient of determination (r2), square root of the mean error ( RMSE).
Model imported from the drc package (Ritz et al., 2016)
Gabriel Danilo Shimizu
Leandro Simoes Azeredo Goncalves
Seber, G. A. F. and Wild, C. J (1989) Nonlinear Regression, New York: Wiley \& Sons (p. 330).
Ritz, C.; Strebig, J.C.; Ritz, M.C. Package ‘drc’. Creative Commons: Mountain View, CA, USA, 2016.
data("emerg")
with(emerg, logistic(time, resp,xlab="Time (days)",ylab="Emergence (%)"))
with(emerg, logistic(time, resp,npar="LL.4",xlab="Time (days)",ylab="Emergence (%)"))