regression | R Documentation |
This function is a simplification of all the analysis functions present in the package.
regression(
trat,
resp,
model = "LM1",
ylab = "Dependent",
xlab = "Independent",
theme = theme_classic(),
legend.position = "top",
point = "all",
textsize = 12,
pointsize = 4.5,
linesize = 0.8,
pointshape = 21,
round = NA,
fontfamily = "sans",
error = "SE",
width.bar = NA,
xname.formula = "x",
yname.formula = "y"
)
trat |
Numeric vector with dependent variable. |
resp |
Numeric vector with independent variable. |
model |
model regression (default is LM1) |
ylab |
Variable response name (Accepts the expression() function) |
xlab |
treatments name (Accepts the expression() function) |
theme |
ggplot2 theme (default is theme_classic()) |
legend.position |
legend position (default is c(0.3,0.8)) |
point |
defines whether you want to plot all points ("all") or only the mean ("mean") |
textsize |
Font size |
pointsize |
shape size |
linesize |
line size |
pointshape |
format point (default is 21) |
round |
round equation |
fontfamily |
Font family |
error |
Error bar (It can be SE - default, SD or FALSE) |
width.bar |
Bar width |
xname.formula |
Name of x in the equation |
yname.formula |
Name of y in the equation |
To change the regression model, change the "model" argument to:
N: Graph for not significant trend.
loess0: Loess non-parametric degree 0
loess1: Loess non-parametric degree 1
loess2: Loess non-parametric degree 2
LM0.5: Quadratic inverse
LM1: Linear regression.
LM2: Quadratic
LM3: Cubic
LM4: Quartic
LM0.5_i: Quadratic inverse without intercept.
LM1_i: Linear without intercept.
LM2_i: Quadratic regression without intercept.
LM3_i: Cubic without intercept.
LM4_i: Quartic without intercept.
LM13: Cubic without beta2
LM13i: Cubic inverse without beta2
LM23: Cubic without beta1
LM23i: Cubic inverse without beta2
LM2i3: Cubic without beta1, with inverse beta3
valcam: Valcam
L3: Three-parameter logistics.
L4: Four-parameter logistics.
L5: Five-parameter logistics.
LL3: Three-parameter log-logistics.
LL4: Four-parameter log-logistics.
LL5: Five-parameter log-logistics.
BC4: Brain-Cousens with four parameter.
BC5: Brain-Cousens with five parameter.
CD4: Cedergreen-Ritz-Streibig with four parameter.
CD5: Cedergreen-Ritz-Streibig with five parameter.
weibull3: Weibull with three parameter.
weibull4: Weibull with four parameter.
GP2: Gompertz with two parameter.
GP3: Gompertz with three parameter.
GP4: Gompertz with four parameter.
VB: Von Bertalanffy
lo3: Lorentz with three parameter
lo4: Lorentz with four parameter
beta: Beta
gaussian3: Analogous to the Gaussian model/Bragg with three parameters.
gaussian4: Analogous to the Gaussian model/Bragg with four parameters.
linear.linear: Linear-linear
linear.plateau: Linear-plateau
quadratic.plateau: Quadratic-plateau
plateau.linear: Plateau-linear
plateau.quadratic: Plateau-Quadratic
log: Logarithmic
log2: Logarithmic quadratic
thompson: Thompson
asymptotic: Exponential
asymptotic_neg: Exponential negative
asymptotic_i: Exponential without intercept.
asymptotic_ineg: Exponential negative without intercept.
biexponential: Biexponential
mitscherlich: Mitscherlich
yieldloss: Yield-loss
hill: Hill
MM2: Michaelis-Menten with two parameter.
MM3: Michaelis-Menten with three parameter.
SH: Steinhart-Hart
page: Page
newton: Newton
potential: Potential
midilli: Midilli
midillim: Modified Midilli
AM: Avhad and Marchetti
peleg: Peleg
VG: Vega-Galvez
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.
library(AgroReg)
data("aristolochia")
attach(aristolochia)
regression(trat, resp)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.