Note that if both x and wĪre missing for a data points, then it is also skipped (by the same rule).Descriptive statistics summarize data. If na.rm = TRUE, then all (x, w) data points for which More precisely, if na.rm = FALSE, then any missing values in either This function handles missing values consistently with WeightedVar(x, w = w) = Hmisc::wtd.var(x, weights = w), The estimator used here is the same as the one used by the "unbiased"Įstimator of the Hmisc package. If NULL, it is estimatedįunction about naming support is remained. If NULL, no subsetting is done.Ĭenter location of the data. Default value is equal weight to all values.Ī vector indicating subset of elements to , useNames = NA )Ī vector of weights the same length as x giving the weights , useNames = NA ) colWeightedSds ( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE. , useNames = NA ) rowWeightedSds ( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE. , useNames = NA ) colWeightedVars ( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE. ) rowWeightedVars ( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE. WeightedVar ( x, w = NULL, idxs = NULL, na.rm = FALSE, center = NULL. x_OP_y: Fast calculation of 'z weightedVar: Weighted variance and weighted standard deviation.weightedMad: Weighted Median Absolute Deviation (MAD).varDiff: Estimation of scale based on sequential-order differences.sum2: Fast sum over subset of vector elements.signTabulate: Calculates the number of negative, zero, positive and missing.rowWeightedMedians: Calculates the weighted medians for each row (column) in a.rowWeightedMeans: Calculates the weighted means for each row (column) in a.rowVars: Variance estimates for each row (column) in a matrix.rowTabulates: Tabulates the values in a matrix by row (column).rowSums2: Calculates the sum for each row (column) in a matrix.rowSds: Standard deviation estimates for each row (column) in a.rowRanks: Gets the rank of the elements in each row (column) of a.rowRanges: Gets the range of values in each row (column) of a matrix.rowQuantiles: Estimates quantiles for each row (column) in a matrix.rowProds: Calculates the product for each row (column) in a matrix.rowOrderStats: Gets an order statistic for each row (column) in a matrix.rowMedians: Calculates the median for each row (column) in a matrix.rowMeans2: Calculates the mean for each row (column) in a matrix.rowLogSumExps: Accurately computes the logarithm of the sum of exponentials.rowIQRs: Estimates of the interquartile range for each row (column) in.rowDiffs: Calculates difference for each row (column) in a matrix.rowCumsums: Cumulative sums, products, minima and maxima for each row.
rowCounts: Counts the number of occurrences of a specific value.rowCollapse: Extracts one cell per row (column) from a matrix.rowAvgsPerColSet: Applies a row-by-row (column-by-column) averaging function to.rowAlls: Checks if a value exists / does not exist in each row.mean2: Fast averaging over subset of vector elements.matrixStats-package: Package matrixStats.logSumExp: Accurately computes the logarithm of the sum of exponentials.indexByRow: Translates matrix indices by rows into indices by columns.binMeans: Fast mean calculations in non-overlapping bins.binCounts: Fast element counting in non-overlapping bins.anyMissing: Checks if there are any missing values in an object or not.allocMatrix: Allocates an empty vector, matrix or array.
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