View source: R/weibull_analysis.R
weibull | R Documentation |
The w3' and 'w4' logistical models provide Weibull. This model was extracted from the 'drc' package.
weibull(
trat,
resp,
npar = "w3",
sample.curve = 1000,
ylab = "Dependent",
xlab = "Independent",
theme = theme_classic(),
legend.position = "top",
r2 = "all",
ic = FALSE,
fill.ic = "gray70",
alpha.ic = 0.5,
error = "SE",
point = "all",
width.bar = NA,
scale = "none",
textsize = 12,
pointsize = 4.5,
linesize = 0.8,
linetype = 1,
pointshape = 21,
fillshape = "gray",
colorline = "black",
round = NA,
yname.formula = "y",
xname.formula = "x",
comment = NA,
fontfamily = "sans"
)
trat |
Numeric vector with dependent variable. |
resp |
Numeric vector with independent variable. |
npar |
Number of model parameters (default is w3) |
sample.curve |
Provide the number of observations to simulate curvature (default is 1000) |
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 "top") |
r2 |
Coefficient of determination of the mean or all values (default is all) |
ic |
Add interval of confidence |
fill.ic |
Color interval of confidence |
alpha.ic |
confidence interval transparency level |
error |
Error bar (It can be SE - default, SD or FALSE) |
point |
Defines whether you want to plot all points ("all") or only the mean ("mean") |
width.bar |
Bar width |
scale |
Sets x scale (default is none, can be "log") |
textsize |
Font size |
pointsize |
Shape size |
linesize |
Line size |
linetype |
line type |
pointshape |
Format point (default is 21) |
fillshape |
Fill shape |
colorline |
Color lines |
round |
round equation |
yname.formula |
Name of y in the equation |
xname.formula |
Name of x in the equation |
comment |
Add text after equation |
fontfamily |
Font family |
The three-parameter Weibull model is given by the expression
y = d\exp(-\exp(b(\log(x)-e)))
Fixing the lower limit at 0 yields the four-parameter model
y = c + (d-c) (1 - \exp(-\exp(b(\log(x)-\log(e)))))
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.
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. and Ritz, M.C. Package ‘drc’. Creative Commons: Mountain View, CA, USA, 2016.
LL, CD,GP
library(AgroReg)
data("aristolochia")
attach(aristolochia)
weibull(trat,resp)
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