I have 2 datasets on sea surface temperature (SST) and the maximum
chlorophyll-specific carbon fixation rate in a water column (Pbm). How can i propose an algorithm that describes the connection between them? Simple linear regression gives poor results (correlation is 0,6 at best). Is there a scientific way to find this way?
The problem you mentioned is a real headache. Sometimes, one arbitrarily tries the best possible adjustment of types for example power, logarithmic, exponential, etc... but there is software that can offer you other more elaborate types of adjustment.
You should also try tricks such as dividing one variable by the second and plotting the ratio as a function of one of the variables and seeing what type of curve you get. You should also try to plot the root of one variable as a function of the other and see how the curve looks. You must also try to plot the logarithm or the exponential of one variable as a function of the other, etc...
Sometimes it is this kind of procedure that gives a good result. It's long and tedious.
Regards
Thank you for your answer. I'll try following your advice!
Do you have any software recommendations? I've been using matlab and plain excel.
Best wishes
Dear Aleksandra,
You have to try the "Origin" software. It is an extraordinary piece of software that has an array of adjustment types. What's nice is that for each adjustment it makes, it gives you the look of the graph that you can compare to yours to see if it matches.
In principle, you can download the trial version from the following link:
https://www.originlab.com/
Regards
With this easy to use software you can easily fit your data with different models:
www.lerenisplezant.be/fitting.htm
Do you have an idea how the relationship between your variables should be? Maybe logistic?
Your program is very interesting, thanks for the offer! I tried linear regression, multiple regression with one more parameter involved. In the literature, it is proposed to approximate this relationship as a seventh-order polynomial function, however, as practice has shown, the results are hardly satisfactory.
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