SH: Analysis: Steinhart-Hart

In AgroReg: Regression Analysis Linear and Nonlinear for Agriculture

Analysis: Steinhart-Hart

Description

The Steinhart-Hart model. The Steinhart-Hart equation is a model used to explain the behavior of a semiconductor at different temperatures, however, Zhai et al. (2020) used this model to relate plant density and grain yield.

Usage

SH(
  trat,
  resp,
  initial = NA,
  sample.curve = 1000,
  ylab = "Dependent",
  xlab = "Independent",
  theme = theme_classic(),
  legend.position = "top",
  r2 = "all",
  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"
)

Arguments

trat	Numeric vector with dependent variable.
resp	Numeric vector with independent variable.
initial	Starting estimates
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)
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

Details

The model function for the Steinhart-Hart model is:

y = \frac{1}{A+B \times ln(x)+C \times ln(x)^3}

Value

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.

Author(s)

Gabriel Danilo Shimizu

Leandro Simoes Azeredo Goncalves

References

Zhai, L., Li, H., Song, S., Zhai, L., Ming, B., Li, S., ... & Zhang, L. (2021). Intra-specific competition affects the density tolerance and grain yield of maize hybrids. Agronomy Journal, 113(1), 224-23. doi:10.1002/agj2.20438

See Also

LL, CD,GP

Examples

library(AgroReg)
data("aristolochia")
attach(aristolochia)
SH(trat,resp)

AgroReg documentation built on May 29, 2024, 9:13 a.m.