Jim Slonder - 4 months ago 12

R Question

I want to use

`mapply`

`fun`

`mapply`

`fun <- function(theta, mat, i, j){`

sum_nearby <- function(mat,i,j,dist){

if (j - dist < 1) mat[i, j + dist]

else if (j + dist > ncol(mat)) mat[i, j - dist]

else mat[i, j - dist] + mat[i, j + dist]

}

g0 <- -2*mat[i,j]

g1 <- g0*sum_nearby(mat,i,j,1)

-log1p(exp(theta %*% c(g0, g1)))

}

Answer

Try `mapply`

over the row and column indices like this where `fun`

is the function defined in the question. The result is a numeric vector `v`

:

```
# test inputs
theta <- 1:2
mat <- as.matrix(BOD)
v <- mapply(fun, row(mat), col(mat), MoreArgs = list(theta = theta, mat = mat))
```

Then it can be summed like this `sum(v)`

or reshaped into a matrix with the same dimensions as `mat`

like this: `replace(mat, TRUE, v)`

or `array(v, dim(mat))`

or `matrix(v, nrow(mat))`

or `0*mat+v`

**Note:** Alternatives would be to use `outer`

returning a matrix having the same dimensions as `mat`

:

```
outer(1:nrow(mat), 1:ncol(mat), Vectorize(function(i, j) fun(theta, mat, i, j)))
```

or `apply`

returning a vector as in `mapply`

solution above:

```
apply(cbind(c(row(mat)), c(col(mat))), 1, function(ix) fun(theta, mat, ix[1], ix[2]))
```