LM_model {seedreg}

Analysis: Linear regression graph

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",
  width.bar = NA,
  scale = "none",
  textsize = 12,
  pointsize = 4.5,
  linesize = 0.8,
  pointshape = 21,
  font.family = "sans"
)

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")

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)

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

VIF

Variance inflation factor (multicollinearity)

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)

Gabriel Danilo Shimizu

Leandro Simoes Azeredo Goncalves

Examples

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

#================================
# Germination
#================================
LM_model(trat,germ, grau=3)

#================================
# Germination speed
#================================
LM_model(trat, vel, grau=3,
ylab=expression("v"~(dias^-1)))