Description Usage Arguments Details Value Author(s) See Also Examples

These functions perform calculation of summary statistics over matrix rows and columns, for each level of a grouping variable (optionally), and with implicit row/column scaling and centering if desired.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
## S4 method for signature 'ANY'
colStats(x, stat, groups,
na.rm = FALSE, tform = identity,
col.center = NULL, col.scale = NULL,
row.center = NULL, row.scale = NULL,
drop = TRUE, BPPARAM = bpparam(), ...)
## S4 method for signature 'ANY'
rowStats(x, stat, groups,
na.rm = FALSE, tform = identity,
col.center = NULL, col.scale = NULL,
row.center = NULL, row.scale = NULL,
drop = TRUE, BPPARAM = bpparam(), ...)
``` |

`x` |
A matrix on which to calculate summary statistics. |

`stat` |
The name of summary statistics to compute over the rows or columns of a matrix. Allowable values include: "min", "max", "prod", "sum", "mean", "var", "sd", "any", "all", and "nnzero". |

`groups` |
A factor or vector giving the grouping. If not provided, no grouping will be used. |

`na.rm` |
If |

`tform` |
A dimensionality-preserving transformation to be applied to the matrix (e.g., |

`col.center` |
A vector of column centers to substract from each row. (Or a matrix with a column for each level of |

`col.scale` |
A vector of column scaling factors to divide from each row. (Or a matrix with a column for each level of |

`row.center` |
A vector of row centers to substract from each column. (Or a matrix with a column for each level of |

`row.scale` |
A vector of row centers to scaling factors to divide from each column. (Or a matrix with a column for each level of |

`drop` |
If only a single summary statistic is calculated, return the results as a vector (or matrix) rather than a list. |

`BPPARAM` |
An optional instance of |

`...` |
Additional arguments. |

The summary statistics methods are calculated over chunks of the matrix using `colstreamStats`

and `rowstreamStats`

. For `matter`

objects, the iteration is performed over the major dimension for IO efficiency.

A list for each `stat`

requested, where each element is either a vector (if no grouping variable is provided) or a matrix where each column corresponds to a different level of `groups`

.

If `drop=TRUE`

, and only a single statistic is requested, then the result will be unlisted and returned as a vector or matrix.

Kylie A. Bemis

1 2 3 4 5 6 7 8 9 |

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