trendline: Add Trendline and Show Equation to Plot

In PhDMeiwp/basicTrendline: Add Trendline and Confidence Interval of Basic Regression Models to Plot

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)

PhDMeiwp/basicTrendline documentation built on May 7, 2022, 9:38 a.m.