Hi all, I am attempting to make a scatterplot of CO2 rate data (y) at varying temperatures (x) with two categorical variables, depth (Mineral, Organic) and substrate (Calcareous, Metapelite, Peridotite) with fitted lines following the equation y = a*exp(B*t) where y = co2 rate, a = basal respiration (intercept), B = slope and t = temperature (time equivalent). I have already fitted all of the exponential curves so I have the values for y, a, B and t for each data point. I am struggling to figure out how to fit the exponential curves across the two groups. So far, I have produced the base scatterplot using GGplot2 colouring by depth and faceting by substrate but I do not know what the best approach is to fit the curves. I have attempted to filter the dataset into categories (substrate = 1, depth = 1) and use nls to fit the curves with such little success that it isn't worth posting the code. Any advice/ guidance is greatly appreciated.
You might look at how response surfaces are plotted in R. This is under the heading of response surface analysis. Good luck, David Booth
To get the exponential curve function from the fitted parameters, you should define
exp_funct
I think you can expect more and faster R coding-related answers if you post your question on websites such as https://stackoverflow.com/
- Badges
- Science topic
- Similar topics
- Mathematical Sciences
- Statistics
- Statistical Software
- SPSS