CD_model: Analysis: Logistic regression Cedergreen-Ritz-Streibig model

In seedreg: Regression Analysis for Seed Germination as a Function of Temperature

Analysis: Logistic regression Cedergreen-Ritz-Streibig model

Description

The 'CRS.4' and 'CRS.5' logistical models provide Brain-Cousens modified logistical models to describe u-shaped hormesis. This model was extracted from the 'drc' package and adapted for temperature analysis in seed germination

Usage

CD_model(
  trat,
  resp,
  npar = "CRS.4",
  error = "SE",
  ylab = "Germination (%)",
  xlab = expression("Temperature ("^"o" * "C)"),
  theme = theme_classic(),
  legend.position = "top",
  cardinal = 0,
  r2 = "all",
  width.bar = NA,
  scale = "none",
  textsize = 12,
  pointsize = 4.5,
  linesize = 0.8,
  pointshape = 21,
  font.family = "sans"
)

Arguments

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_classic())
legend.position	legend position (default is c(0.3,0.8))
cardinal	defines the value of y considered extreme (default considers 0 germination)
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
pointsize	shape size
linesize	line size
pointshape	format point (default is 21)
font.family	Font family (default is sans)

Details

The four-parameter model is given by the expression:

f(x) = 0 + \frac{d-0+f \exp(-1/x)}{1+\exp(b(\log(x)-\log(e)))}

while the five-parameter is:

f(x) = c + \frac{d-c+f \exp(-1/x)}{1+\exp(b(\log(x)-\log(e)))}

Value

Coefficients

Coefficients and their p values

Optimum temperature

Optimum temperature (equivalent to the maximum point)

Optimum temperature response

Response at the optimal temperature (equivalent to the maximum point)

Minimal temperature

Temperature that has the lowest response

Minimal temperature response

Lowest predicted response

Predicted maximum basal value

Lower basal limit temperature based on the value set by the user (default is 0)

Predicted minimum basal value

Upper basal limit temperature based on the value set by the user (default is 0)

AIC

Akaike information criterion

BIC

Bayesian Inference Criterion

r-squared

Determination coefficient

RMSE

Root mean square error

grafico

Graph in ggplot2 with equation

Note

If the maximum predicted value is equal to the maximum x, the curve does not have a maximum point within the studied range. If the minimum value is less than the lowest point studied, disregard the value.

Author(s)

Model imported from the drc package (Ritz et al., 2016)

Gabriel Danilo Shimizu

Leandro Simoes Azeredo Goncalves

References

Seber, G. A. F. and Wild, C. J (1989) Nonlinear Regression, New York: Wiley and Sons (p. 330).

Ritz, C.; Strebig, J.C.; Ritz, M.C. Package 'drc'. Creative Commons: Mountain View, CA, USA, 2016.

Examples

library(seedreg)
data("aristolochia")
attach(aristolochia)

#================================
# Germination
#================================
CD_model(trat,germ)

#================================
# Germination speed
#================================
CD_model(trat, vel, ylab=expression("v"~(dias^-1)))

seedreg documentation built on July 8, 2022, 1:08 a.m.