Display a pairwise scatter plot of two datasets for a random selection of variables. If the second dataset is not given, the function displays a histogram with normal curve superposition.
pairwiseMatrix(x, y = NULL, size = nrow(x), r = 4, c = 4, ...)Arguments
- x
A matrix or data.frame (n x p) of continuous data.
- y
A matrix or data.frame (n x q) of continuous data.
- size
number of rows to be sampled (default
size = nrow(x)).- r
number of rows of the plot layout (default
r = 4).- c
number of columns of the plot layout (default
c = 4).- ...
Currently ignored.
Value
No return value
Examples
adjdata <- SEMbap(sachs$graph, log(sachs$pkc))$data
#> DAG conversion : TRUE
#> Bow-free covariances search. Use method: cggm ...
#> Number of bow-free covariances / df : 4 / 37
#> Max parent set(S) / Sparsity idx(s) : 5 / 18
#> Number of clusters / number of nodes: 3 / 6
#>
rawdata <- log(sachs$pkc)
pairwiseMatrix(adjdata, rawdata, size = 1000)
