R語言進行曲線/直線趨勢線擬合並計算P值、添加置信區間

8/26/2021 3:39:51 PM

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在對一些時間序列數據進行線性擬合的時候，最方便的是在Excel中添趨勢線，同時顯示公式與R值，但是我們需要對其進行P值計算以檢驗該趨勢是否具有顯著性，此外，置信區間也是一個需要考慮是否進行顯示的問題。

library(basicTrendline) 
library(readxl)
#讀取的excel文件中只有兩列數據，"year"和"area"
data <- read_excel("D:/00GBAWater/06CODE/df.xlsx")
x <- c(1, 3, 6,  9,  13,   17)
y <- c(5, 8, 11, 13, 13.2, 13.5)

直線擬合：默認（自動添加95%置信區間）

trendline(data$year,data$area, model="line2P", ePos.x = "topleft", summary=TRUE, eDigit=5)

使用

trendline(x, y, model = "line2P", Pvalue.corrected = TRUE,
        linecolor = "blue", lty = 1, lwd = 1, 
        show.equation = TRUE, show.Rpvalue = 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 = "grey",    CI.alpha = 1, CI.lty = 1, CI.lwd = 1, 
        las = 1, xlab = NULL, ylab = NULL, ...)

主要參數設置

model = "xxx"

• “line2P” (formula as: y=a*x+b),
• “line3P” (y=ax2+bx+c),
• “log2P” (y=a*ln(x)+b),
• “exp2P” (y=aebx),
• “exp3P” (y=aebx+c),
• “power2P” (y=a*xb),
• “power3P” (y=a*xb+c).

參考鏈接：

http://blog.sciencenet.cn/blog-651374-1126673.html