Renata Diaz 8/22/2019
## Loading in data version 1.90.0
## Warning in bind_rows_(x, .id): binding factor and character vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Loading required package: polynom
This seems to match intuition from the coefficients plot. I'm not completely sure but I think the euclidean distance to all other points (above) is weird for a couple reasons; one being it's not actually being calculated to all other points; I just cycled forward two ticks. So every point gets compared to 2 other points, I guess? i + 2 and i - 2.
## # A tibble: 6 x 5
## sim_source sim varname coefficient varindex
## <chr> <int> <chr> <dbl> <int>
## 1 mete 1 (Intercept) 0.0928 1
## 2 mete 2 (Intercept) 0.0815 1
## 3 mete 3 (Intercept) 0.0856 1
## 4 mete 4 (Intercept) 0.0515 1
## 5 mete 5 (Intercept) 0.0606 1
## 6 mete 6 (Intercept) 0.0489 1
(want to somehow downweight really big abundance values? but euclidean distance in log space seems highly suspect, and I don't really have intuition for interpreting the results)
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