trendline {basicTrendline} | R Documentation |

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.

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, ... )

`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: |

`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 |

`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 |

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))".

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).

Weiping Mei, Guangchuang Yu

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.

`trendline`

, `SSexp3P`

, `SSpower3P`

, `nls`

, `selfStart`

, `plotFit`

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]