R/mpm_median.R
mpm_median.RdCalculates an element-wise median over a list of matrices or CompadreMat objects of constant dimension.
mat_median(x, na.rm = FALSE)
mpm_median(x, na.rm = FALSE)A list of matrices or, for mpm_sd a list of `CompadreMat` objects,
all of the same dimension
Logical indicating whether missing values should be excluded
(see Details). Defaults to FALSE.
A matrix containing the median of each element across all matrices in the list
The difference between function mat_median) and (mpm_median is that
mat_median takes input as a list of matrices (e.g., a list of **A**
matrices) while mat_median takes input as a list of `CompadreMat` objects and
thus calculates the mean matrices for both the **A** matrix and its
submatrices (**U**, **F**, **C**).
If na.rm == TRUE, missing values are ignored in the calculation of the
mean matrix. If na.rm == TRUE and a given element is NA in
every matrix within x, the value returned for that element will
be 0.
Other data management:
cdb_flatten(),
cdb_id_stages(),
cdb_id_studies(),
cdb_id(),
cdb_mean_matF(),
cdb_rbind(),
cdb_unflatten(),
cdb_unnest(),
mat_elementwise_apply(),
mpm_mean(),
mpm_sd(),
string_representation
# set seed for repeatability
set.seed(42)
# create a function that generates a matrix with random values
create_matrix <- function() {
matrix(runif(9, 0, 1), nrow = 3)
}
# use replicate() to call the create_matrix() function 20 times
mat_list <- replicate(20, create_matrix(), simplify = FALSE)
# get the median matrix
mat_median(mat_list)
#> [,1] [,2] [,3]
#> [1,] 0.5731547 0.7219267 0.5627341
#> [2,] 0.5862329 0.5077667 0.5146376
#> [3,] 0.5720870 0.4575122 0.6933612
# If the matrices are in an RCompadre object, extract them using `matA` before
# passing to `mat_median`
my_compadre <- cdb_build_cdb(mat_a = mat_list)
#> Warning: Metadata does not include a `SpeciesAccepted` column, so number
#> of species not provided when viewing object.
mat_median(matA(my_compadre))
#> [,1] [,2] [,3]
#> [1,] 0.5731547 0.7219267 0.5627341
#> [2,] 0.5862329 0.5077667 0.5146376
#> [3,] 0.5720870 0.4575122 0.6933612