NDD - 10 months ago 65

R Question

I have searched for an answer or a solution to this task with no success as of yet, so I do apologize if this is redundant.

I want to randomize the data between two columns. This is to simulate species misidentification in vegetation field data, so I want to assign some sort of probability of misidentification between the two columns as well. I would imagine that there is some way to do this using

`sample`

I will select some readily available data for an example.

`library (vegan)`

data (dune)

If you type

`head (dune)`

`poa = data.frame(Poaprat=dune$Poaprat,Poatriv=dune$Poatriv)`

head(poa)

Poaprat Poatriv

1 4 2

2 4 7

3 5 6

4 4 5

5 2 6

6 3 4

What would be the best way to randomize the values between these two columns (transferring between each other and/or adding to one when both are present). The resulting data may look like:

`Poaprat Poatriv`

1 6 0

2 4 7

3 5 6

4 5 4

5 0 7

6 4 3

P.S.

For the cringing ecologist out there: please realize, I have made this example in the interest of time and that I know relative cover values are not additive. I apologize for needing to do that.

*** Edit: For more clarity, the type of data being randomized would be percent cover estimates (so values between 0% and 100%). The data in this quick example are relative cover estimates, not counts.

Answer Source

You'll still need to replace the actual columns with the new ones and there may be a more elegant way to do this (it's late in EDT land) *and* you'll have to decide what else besides the normal distribution you'll want to use (i.e. how you'll replace `sample()`

) **but** you get your swaps and adds with:

```
library(vegan)
library(purrr)
data(dune)
poa <- data.frame(
Poaprat=dune$Poaprat,
Poatriv=dune$Poatriv
)
map2_df(poa$Poaprat, poa$Poatriv, function(x, y) {
for (i in 1:length(x)) {
what <- sample(c("left", "right", "swap"), 1)
switch(
what,
left={
x[i] <- x[i] + y[i]
y[i] <- 0
},
right={
y[i] <- x[i] + y[i]
x[i] <- 0
},
swap={
tmp <- y[i]
y[i] <- x[i]
x[i] <- tmp
}
)
}
data.frame(Poaprat=x, Poatriv=y)
})
```