I need some help getting pointed in the right direction for creating a regression model in R with data that looks like this.
This is my first foray into this. So using Excel's trend line equation as my reference, I was able to create a logarithmic trend line for another set of data which matched between the two applications.
However, with this specific example, I'm not sure how to formulate the model or even if I should be using non-linear vs linear regression with transformation. Below is an example of the data in the plot.
x = c(0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1) y = c(0.008,0.004,0.0025,0.0024,0.0023,0.0022,0.0021,0.002,0.0018,0.0005,0.012,0.006, 0.00375,0.0036,0.00345,0.0033,0.00315,0.003,0.0027,0.00075) z = c(1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2) df = data.frame(x, y, z) plot(df$y ~ df$x, type="p", pch=20, col=df$z)