# big_cor: Correlation In bigstatsr: Statistical Tools for Filebacked Big Matrices

 big_cor R Documentation

## Correlation

### Description

Compute the (Pearson) correlation matrix of a Filebacked Big Matrix.

### Usage

```big_cor(
X,
ind.row = rows_along(X),
ind.col = cols_along(X),
block.size = block_size(nrow(X))
)
```

### Arguments

 `X` An object of class FBM. `ind.row` An optional vector of the row indices that are used. If not specified, all rows are used. Don't use negative indices. `ind.col` An optional vector of the column indices that are used. If not specified, all columns are used. Don't use negative indices. `block.size` Maximum number of columns read at once. Default uses block_size.

### Value

A temporary FBM, with the following two attributes:

• a numeric vector `center` of column scaling,

• a numeric vector `scale` of column scaling.

### Matrix parallelization

Large matrix computations are made block-wise and won't be parallelized in order to not have to reduce the size of these blocks. Instead, you may use Microsoft R Open or OpenBLAS in order to accelerate these block matrix computations. You can also control the number of cores used with `bigparallelr::set_blas_ncores()`.

cor big_crossprodSelf

### Examples

```X <- FBM(13, 17, init = rnorm(221))

# Comparing with cor
K <- big_cor(X)
class(K)
dim(K)
K\$backingfile

true <- cor(X[])
all.equal(K[], true)

# Using only half of the data
n <- nrow(X)
ind <- sort(sample(n, n/2))
K2 <- big_cor(X, ind.row = ind)

true2 <- cor(X[ind, ])
all.equal(K2[], true2)
```

bigstatsr documentation built on Oct. 14, 2022, 9:05 a.m.