linear.linear {AgroReg}

Analysis: Linear-Linear

Description

This function performs linear linear regression analysis.

Usage

linear.linear(
  trat,
  resp,
  middle = 1,
  CI = FALSE,
  bootstrap.samples = 1000,
  sig.level = 0.05,
  error = "SE",
  ylab = "Dependent",
  xlab = "Independent",
  theme = theme_classic(),
  point = "all",
  width.bar = NA,
  legend.position = "top",
  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.

middle

A scalar in [0,1]. This represents the range that the change-point can occur in. 0 means the change-point must occur at the middle of the range of x-values. 1 means that the change-point can occur anywhere along the range of the x-values.

CI

Whether or not a bootstrap confidence interval should be calculated. Defaults to FALSE because the interval takes a non-trivial amount of time to calculate

bootstrap.samples

The number of bootstrap samples to take when calculating the CI.

sig.level

What significance level to use for the confidence intervals.

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())

point

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

width.bar

Bar width

legend.position

legend position (default is "top")

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-linear model is defined by: First curve:

y = \beta_0 + \beta_1 \times x (x < breakpoint)

Second curve:

y = \beta_0 + \beta_1 \times breakpoint + w \times x (x > breakpoint)

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); breakpoint and the graph using ggplot2 with the equation automatically.

Author(s)

Model imported from the SiZer package

Gabriel Danilo Shimizu

Leandro Simoes Azeredo Goncalves

References

Chiu, G. S., R. Lockhart, and R. Routledge. 2006. Bent-cable regression theory and applications. Journal of the American Statistical Association 101:542-553.

Toms, J. D., and M. L. Lesperance. 2003. Piecewise regression: a tool for identifying ecological thresholds. Ecology 84:2034-2041.

See Also

quadratic.plateau, linear.plateau

Examples

library(AgroReg)
data("granada")
attach(granada)
linear.linear(time,WL)