LM_model: Analysis: Linear regression graph

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

Description

Linear regression analysis of an experiment with a quantitative factor or isolated effect of a quantitative factor

Usage

LM_model(
  trat,
  resp,
  ylab = "Germination (%)",
  error = "SE",
  xlab = expression("Temperature ("^"o" * "C)"),
  grau = NA,
  theme = theme_classic(),
  cardinal = 0,
  legend.position = "top",
  scale = "none"
)

Arguments

trat	Numerical vector with treatments (Declare as numeric)
resp	Numerical vector containing the response of the experiment.
ylab	Dependent variable name (Accepts the expression() function)
error	Error bar (It can be SE - default, SD or FALSE)
xlab	Independent variable name (Accepts the expression() function)
grau	degree of the polynomial (1,2 or 3)
theme	ggplot2 theme (default is theme_classic())
cardinal	defines the value of y considered extreme (default considers 0 germination)
legend.position	legend position (default is "top")
scale	Sets x scale (default is none, can be "log")

Value

The function returns the coefficients and respective p-values; statistical parameters such as AIC, BIC, R2, VIF; cardinal and optimal temperature and the graph using ggplot2 with the 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)

Gabriel Danilo Shimizu

Leandro Simoes Azeredo Goncalves

Examples

library(seedreg)
data("aristolochia")
attach(aristolochia)
LM_model(trat,resp, grau = 3)

AgronomiaR/seedreg documentation built on May 19, 2021, 12:12 p.m.