# matrixStats v0.55.0

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## Functions that Apply to Rows and Columns of Matrices (and to Vectors)

High-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized. There are also optimized vector-based methods, e.g. binMeans(), madDiff() and weightedMedian().

## Functions in matrixStats

Name | Description | |

logSumExp | Accurately computes the logarithm of the sum of exponentials | |

allocMatrix | Allocates an empty vector, matrix or array | |

anyMissing | Checks if there are any missing values in an object or not | |

diff2 | Fast lagged differences | |

matrixStats-package | Package matrixStats | |

indexByRow | Translates matrix indices by rows into indices by columns | |

binCounts | Fast element counting in non-overlapping bins | |

binMeans | Fast mean calculations in non-overlapping bins | |

mean2 | Fast averaging over subset of vector elements | |

rowAlls | Checks if a value exists / does not exist in each row (column) of a matrix | |

rowLogSumExps | Accurately computes the logarithm of the sum of exponentials across rows or columns | |

rowOrderStats | Gets an order statistic for each row (column) in a matrix | |

rowMedians | Calculates the median for each row (column) in a matrix | |

rowCounts | Counts the number of occurrences of a specific value | |

rowCumsums | Cumulative sums, products, minima and maxima for each row (column) in a matrix | |

rowAvgsPerColSet | Applies a row-by-row (column-by-column) averaging function to equally-sized subsets of matrix columns (rows) | |

rowCollapse | Extracts one cell per row (column) from a matrix | |

rowMeans2 | Calculates the mean for each row (column) in a matrix | |

rowQuantiles | Estimates quantiles for each row (column) in a matrix | |

product | Calculates the product for each row (column) in a matrix | |

rowWeightedMeans | Calculates the weighted means for each row (column) in a matrix | |

rowWeightedMedians | Calculates the weighted medians for each row (column) in a matrix | |

rowRanks | Gets the rank of the elements in each row (column) of a matrix | |

rowRanges | Gets the range of values in each row (column) of a matrix | |

rowVars | Variance estimates for each row (column) in a matrix | |

rowTabulates | Tabulates the values in a matrix by row (column). | |

rowMads | Standard deviation estimates for each row (column) in a matrix | |

rowDiffs | Calculates difference for each row (column) in a matrix | |

rowSums2 | Calculates the sum for each row (column) in a matrix | |

rowIQRs | Estimates of the interquartile range for each row (column) in a matrix | |

weightedMedian | Weighted Median Value | |

weightedVar | Weighted variance and weighted standard deviation | |

signTabulate | Calculates the number of negative, zero, positive and missing values | |

sum2 | Fast sum over subset of vector elements | |

weightedMad | Weighted Median Absolute Deviation (MAD) | |

x_OP_y | Fast calculation of 'z <- x OP y' and 'z <- t(t(x) OP y)' | |

validateIndices | Validate indices | |

varDiff | Estimation of scale based on sequential-order differences | |

weightedMean | Weighted Arithmetic Mean | |

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## Vignettes of matrixStats

Name | ||

matrixStats-methods.md.rsp | ||

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## Last month downloads

## Details

VignetteBuilder | R.rsp |

License | Artistic-2.0 |

LazyLoad | TRUE |

NeedsCompilation | yes |

ByteCompile | TRUE |

URL | https://github.com/HenrikBengtsson/matrixStats |

BugReports | https://github.com/HenrikBengtsson/matrixStats/issues |

RoxygenNote | 6.1.1 |

Packaged | 2019-09-06 06:24:24 UTC; hb |

Repository | CRAN |

Date/Publication | 2019-09-07 16:50:15 UTC |

suggests | base64enc , ggplot2 , knitr , microbenchmark , R.devices , R.rsp |

depends | R (>= 2.12.0) |

Contributors | Dongcan Jiang, Peter Langfelder, Hector Corrada Bravo, Robert Gentleman, Harris Jaffee, Ola Hossjer, Peter Hickey, Brian Montgomery |

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