Kernels

I finally got the model working! The kernel looks good and its graph is pretty (below). I’ve used some iterative code to find the model’s stable population growth rate, stable stage distribution, and reproductive value vector. I have not used a very large matrix due to the computing limitations of my laptop, but I can easily transfer my code to a more powerful computer when it becomes necessary.

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Progress

I’ve created a regression for converting dbh to height and it’s working pretty well. One issue with it is that when I combine the data for young trees (which were measured in height) and bigger trees (which I converted), there is very little variance among the heights of larger trees; the conversion has served as a smoother of the data. This makes a regression for growth fit much more nicely, but unfortunately also creates an uneven distribution of residuals. I have attached a variance to the conversion to add some variance among its outputs, but there is still a skew in the residuals. I am currently looking into implications this may have.

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DBH to Height

I’ve spent the last week making regressions for different data in R. Actually using R and manipulating data is quite easy. The hard part is trying to get good data. There are multiple years of data entered by multiple people at different times and in different ways. The result is a bit of a nightmare when it comes to using the data (and I have, in fact, had nightmares about it). There are some trees that have a diameter at breast height( DBH) but are only a foot high, there are some trees that have the same ID number as a different tree, and there are some trees that have simply gone missing. A big part of this summer will be finding if the funky data are from something being lost in conversion from PDF to Excel, or if there were errors recording data in the field.

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