Alejandro Jiménez Rico - 9 months ago 61

R Question

I have a matrix like this:

I would like to sum every value of a single row but with a ponderation.

Example: Given a specific row, the sum would be:

`S = x1 * loan + x2 * mortdue + x3 * value + ...`

`x1, x2, x3, ...`

I tried

`rowSums()`

Answer

You are looking for a matrix-vector multiplication. For example, if you have a matrix:

```
set.seed(0)
A <- matrix(round(rnorm(9), 1), 3)
# [,1] [,2] [,3]
#[1,] 1.3 1.3 -0.9
#[2,] -0.3 0.4 -0.3
#[3,] 1.3 -1.5 0.0
```

And you have another vector `x`

, which is what you called "ponderation":

```
x <- round(rnorm(3), 1)
#[1] 2.4 0.8 -0.8
```

You can do

```
drop(A %*% x)
#[1] 4.88 -0.16 1.92
```

The `drop`

just convert the result single column matrix into a 1D vector.

You can have a quick check to see this is what you want:

```
sum(A[1, ] * x)
#[1] 4.88
sum(A[2, ] * x)
#[1] -0.16
sum(A[3, ] * x)
#[1] 1.92
```

Compared with `rowSums()`

, you can also think such computation as a "weighted rowSums".

At the moment, it seems more likely that you have a data frame rather than a matrix. You can convert this data frame to matrix by `as.matrix()`

.

Source (Stackoverflow)