big_colstats | R Documentation |
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)
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. Don't use negative indices. |
ind.col |
An optional vector of the column indices that are used. If not specified, all columns are used. Don't use negative indices. |
ncores |
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.
colSums apply
set.seed(1) 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))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.