stat_eq {ggtrendline}

Add Equation to 'ggplot'

Description

Add regression equation to 'ggplot', by using different models built in the 'ggtrendline()' function. The function includes the following models:
"line2P" (formula as: y=a*x+b),
"line3P" (y=a*x^2+b*x+c),
"log2P" (y=a*ln(x)+b),
"exp2P" (y=a*exp(b*x)),
"exp3P" (y=a*exp(b*x)+c),
"power2P" (y=a*x^b),
and "power3P" (y=a*x^b+c).

Usage

stat_eq(
  x,
  y,
  model = "line2P",
  show.eq = TRUE,
  xname = "x",
  yname = "y",
  yhat = FALSE,
  eq.x = NULL,
  eq.y = NULL,
  text.col = "black",
  eDigit = 3,
  eSize = 3
)

Arguments

x, y

the x and y arguments provide the x and y coordinates for the 'ggplot'. Any reasonable way of defining the coordinates is acceptable.

model

select which model to fit. Default is "line2P". The "model" should be one of c("line2P", "line3P", "log2P", "exp2P", "exp3P", "power2P", "power3P"), their formulas are as follows:
"line2P": y=a*x+b
"line3P": y=a*x^2+b*x+c
"log2P": y=a*ln(x)+b
"exp2P": y=a*exp(b*x)
"exp3P": y=a*exp(b*x)+c
"power2P": y=a*x^b
"power3P": y=a*x^b+c

show.eq

whether to show the regression equation, the value is one of c("TRUE", "FALSE").

xname

to specify the expression of "x" in equation, i.e., expression('x'), see Examples.

yname

to specify the expression of "y" in equation, i.e., expression('y'), see Examples.

yhat

whether to add a hat symbol (^) on the top of "y" in equation. Default is FALSE.

eq.x, eq.y

equation position.

text.col

the color used for the equation text.

eDigit

the numbers of digits for equation parameters. Default is 3.

eSize

font size of equation. Default is 3.

Details

The values of each parameter of regression model can be found by typing trendline_sum function in this package.

The linear models (line2P, line3P, log2P) in this package are estimated by lm function, while the nonlinear models (exp2P, exp3P, power2P, power3P) are estimated by nls function (i.e., least-squares method).

Value

No return value (called for side effects).

See Also

ggtrendline, stat_rrp, trendline_sum