trendline {basicTrendline}R Documentation

Add Trendline and Show Equation to Plot

Description

Plot, draw regression line and confidence interval, and show regression equation, R-square and P-value, as simple as possible, by using different models built in the 'trendline()' function. The function includes the following models in the latest version: "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). Besides, the summarized result of each fitted model is also output by default.

Usage

trendline(
  x,
  y,
  model = "line2P",
  Pvalue.corrected = TRUE,
  linecolor = "blue",
  lty = 1,
  lwd = 1,
  show.equation = TRUE,
  show.Rsquare = TRUE,
  show.pvalue = TRUE,
  Rname = 1,
  Pname = 0,
  xname = "x",
  yname = "y",
  yhat = FALSE,
  summary = TRUE,
  ePos.x = NULL,
  ePos.y = NULL,
  text.col = "black",
  eDigit = 5,
  eSize = 1,
  CI.fill = TRUE,
  CI.level = 0.95,
  CI.color = "grey90",
  CI.alpha = 1,
  CI.lty = 1,
  CI.lwd = 1,
  las = 1,
  xlab = NULL,
  ylab = NULL,
  ...
)

Arguments

x, y

the x and y arguments provide the x and y coordinates for the plot. 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

Pvalue.corrected

if P-value corrected or not, the value is one of c("TRUE", "FALSE").

linecolor

color of regression line.

lty

line type. lty can be specified using either text c("blank","solid","dashed","dotted","dotdash","longdash","twodash") or number c(0, 1, 2, 3, 4, 5, 6). Note that lty = "solid" is identical to lty=1.

lwd

line width. Default is 1.

show.equation

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

show.Rsquare

whether to show the R-square, the value is one of c("TRUE", "FALSE").

show.pvalue

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

Rname

to specify the character of R-square, the value is one of c(0, 1), corresponding to c(r^2, R^2).

Pname

to specify the character of P-value, the value is one of c(0, 1), corresponding to c(p, P).

xname

to specify the character of "x" in equation, see Examples [case 5].

yname

to specify the character of "y" in equation, see Examples [case 5].

yhat

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

summary

summarizing the model fits. Default is TRUE.

ePos.x, ePos.y

equation position. Default as ePos.x = "topleft". If no need to show equation, set ePos.x = NA. It's same as those in legend.

text.col

the color used for the equation text.

eDigit

the numbers of digits for equation parameters. Default is 5.

eSize

font size in percentage of equation. Default is 1.

CI.fill

fill the confidence interval? (TRUE by default, see 'CI.level' to control)

CI.level

level of confidence interval to use (0.95 by default)

CI.color

line or fill color of confidence interval.

CI.alpha

alpha value of fill color of confidence interval.

CI.lty

line type of confidence interval.

CI.lwd

line width of confidence interval.

las

style of axis labels. (0=parallel, 1=all horizontal, 2=all perpendicular to axis, 3=all vertical)

xlab, ylab

labels of x- and y-axis.

...

additional parameters to plot, such as type, main, sub, pch, col.

Details

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).

The argument 'Pvalue.corrected' is only valid for non-linear regression.

If "Pvalue.corrected = TRUE", the P-value is calculated by using "Residual Sum of Squares" and "Corrected Total Sum of Squares (i.e. sum((y-mean(y))^2))".
If "Pvalue.corrected = FALSE", the P-value is calculated by using "Residual Sum of Squares" and "Uncorrected Total Sum of Squares (i.e. sum(y^2))".

Note

Confidence intervals for nonlinear regression (i.e., objects of class nls) are based on the linear approximation described in Bates & Watts (2007) and Greenwell & Schubert-Kabban (2014).

Author(s)

Weiping Mei, Guangchuang Yu

References

Bates, D. M., and Watts, D. G. (2007) Nonlinear Regression Analysis and its Applications. Wiley.

Greenwell B. M., and Schubert-Kabban, C. M. (2014) investr: An R Package for Inverse Estimation. The R Journal, 6(1), 90-100.

See Also

trendline, SSexp3P, SSpower3P, nls, selfStart, plotFit

Examples

library(basicTrendline)
x <- c(1, 3, 6,  9,  13,   17)
y <- c(5, 8, 11, 13, 13.2, 13.5)

### [case 0]  ggplot2-like trendline by par {graphics}

par(mgp=c(1.5,0.4,0), mar=c(3,3,1,1), tck=-0.01, cex.axis=0.9)

trendline(x, y, "exp3P")

# dev.off()

### [case 1] default
trendline(x, y, model="line2P", ePos.x = "topleft", summary=TRUE, eDigit=5)

### [case 2]  draw lines of confidence interval only (set CI.fill = FALSE)
trendline(x, y, model="line3P", CI.fill = FALSE, CI.color = "black", CI.lty = 2, linecolor = "blue")

### [case 3]  draw trendliine only (set CI.color = NA)
trendline(x, y, model="log2P", ePos.x= "top", linecolor = "red", CI.color = NA)

### [case 4]  show regression equation only
trendline(x, y, model="exp2P", show.Rsquare = FALSE, show.pvalue = FALSE)

### [case 5]  specify the name of parameters in equation
# see Arguments c('xname', 'yname', 'yhat', 'Rname', 'Pname').
trendline(x, y, model="exp3P", xname="T", yname=paste(delta^15,"N"),
          yhat=FALSE, Rname=1, Pname=0, ePos.x = "bottom")

### [case 6]  change the digits, font size, and color of equation.
trendline(x, y, model="power2P", eDigit = 3, eSize = 1.4, text.col = "blue")

### [case 7]  don't show equation (set ePos.x = NA)
trendline(x, y, model="power3P", ePos.x = NA)



[Package basicTrendline version 2.0.5 Index]