`big_cor.Rd`

Compute the correlation matrix of a Filebacked Big Matrix.

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

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. |

ind.col | An optional vector of the column indices that are used.
If not specified, all columns are used. |

block.size | Maximum number of columns read at once. Default uses block_size. |

A temporary FBM, with the following two attributes:

a numeric vector

`center`

of column scaling,a numeric vector

`scale`

of column scaling.

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()`

.

#> [1] "FBM" #> attr(,"package") #> [1] "bigstatsr"dim(K)#> [1] 17 17K$backingfile#> [1] "C:\\Users\\au639593\\AppData\\Local\\Temp\\Rtmpq8tKLv\\file2e34b9f6eaa.bk"#> [1] 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)#> [1] TRUE