LM {AgroReg}

Analysis: Linear, quadratic, quadratic inverse, cubic and quartic

Description

Linear, quadratic, quadratic inverse, cubic and quartic regression.

Usage

LM(
  trat,
  resp,
  degree = NA,
  sample.curve = 1000,
  ylab = "Dependent",
  xlab = "Independent",
  error = "SE",
  ic = FALSE,
  fill.ic = "gray70",
  alpha.ic = 0.5,
  point = "all",
  r2 = "all",
  theme = theme_classic(),
  legend.position = "top",
  width.bar = NA,
  scale = "none",
  textsize = 12,
  pointsize = 4.5,
  linesize = 0.8,
  linetype = 1,
  pointshape = 21,
  fillshape = "gray",
  colorline = "black",
  round = NA,
  xname.formula = "x",
  yname.formula = "y",
  comment = NA,
  fontfamily = "sans"
)

Arguments

trat

Numeric vector with dependent variable.

resp

Numeric vector with independent variable.

degree

degree of the polynomial (0.5, 1, 2, 3 or 4)

sample.curve

Provide the number of observations to simulate curvature (default is 1000)

ylab

Dependent variable name (Accepts the expression() function)

xlab

Independent variable name (Accepts the expression() function)

error

Error bar (It can be SE - default, SD or FALSE)

ic

Add interval of confidence

fill.ic

Color interval of confidence

alpha.ic

confidence interval transparency level

point

defines whether you want to plot all points ("all") or only the mean ("mean")

r2

coefficient of determination of the mean or all values (default is all)

theme

ggplot2 theme (default is theme_classic())

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

linetype

line type

pointshape

format point (default is 21)

fillshape

Fill shape

colorline

Color lines

round

round equation

xname.formula

Name of x in the equation

yname.formula

Name of y in the equation

comment

Add text after equation

fontfamily

Font family

Details

The linear model is defined by:

y = \beta_0 + \beta_1\cdot x

The quadratic model is defined by:

y = \beta_0 + \beta_1\cdot x + \beta_2\cdot x^2

The quadratic inverse model is defined by:

y = \beta_0 + \beta_1\cdot x + \beta_2\cdot x^{0.5}

The cubic model is defined by:

y = \beta_0 + \beta_1\cdot x + \beta_2\cdot x^2 + \beta_3\cdot x^3

The quartic model is defined by:

y = \beta_0 + \beta_1\cdot x + \beta_2\cdot x^2 + \beta_3\cdot x^3+ \beta_4\cdot x^4

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

Examples

library(AgroReg)
data("aristolochia")
attach(aristolochia)
LM(trat,resp, degree = 3)