mitscherlich {AgroReg} | R Documentation |
This function performs Mitscherlich regression analysis.
mitscherlich(
trat,
resp,
initial = NA,
sample.curve = 1000,
ylab = "Dependent",
xlab = "Independent",
theme = theme_classic(),
legend.position = "top",
error = "SE",
r2 = "all",
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. |
initial |
List Initial parameters (A, b, e) |
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") |
error |
Error bar (It can be SE - default, SD or FALSE) |
r2 |
coefficient of determination of the mean or all values (default is all) |
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 Mitscherlich model is defined by:
y = A \times (1-10^{-eb-ex})
where "y" is the yield obtained when "b" units of a nutrient are in the soil and "x" units of it are added as fertilizer, "A" is the maximum yield, and "e" is the proportionality factor, has recently received increasing interest.
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.
Gabriel Danilo Shimizu
Leandro Simoes Azeredo Goncalves
library(AgroReg)
data("granada")
attach(granada)
mitscherlich(time,WL)