big_colstats: Standard univariate statistics

View source: R/colstats.R

big_colstatsR Documentation

Standard univariate statistics


Standard univariate statistics for columns of a Filebacked Big Matrix. For now, the sum and var are implemented (the mean and sd can easily be deduced, see examples).


big_colstats(X, ind.row = rows_along(X), ind.col = cols_along(X), ncores = 1)



An object of class FBM.


An optional vector of the row indices that are used. If not specified, all rows are used. Don't use negative indices.


An optional vector of the column indices that are used. If not specified, all columns are used. Don't use negative indices.


Number of cores used. Default doesn't use parallelism. You may use nb_cores.


Data.frame of two numeric vectors sum and var with the corresponding column statistics.

See Also

colSums apply



X <- big_attachExtdata()

# Check the results
str(test <- big_colstats(X))

# Only with the first 100 rows
ind <- 1:100
str(test2 <- big_colstats(X, ind.row = ind))
plot(test$sum, test2$sum)
abline(lm(test2$sum ~ test$sum), col = "red", lwd = 2)

X.ind <- X[ind, ]
all.equal(test2$sum, colSums(X.ind))
all.equal(test2$var, apply(X.ind, 2, var))

# deduce mean and sd
# note that the are also implemented in big_scale()
means <- test2$sum / length(ind) # if using all rows,
                                 # divide by nrow(X) instead
all.equal(means, colMeans(X.ind))
sds <- sqrt(test2$var)
all.equal(sds, apply(X.ind, 2, sd))

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