Description Usage Arguments Examples
This plot shows what happens to the variance explained by each component if rho is increased. The individual explained variances are neither non-decreasing nor non-increasing. Their sum does trend downwards, but it is also not non-increasing just like the proportion of explained variance.
1 2 3 4 5 6 7 8 9 | gpower_comp_var_plot(
data,
k,
intervals,
reg = "l1",
center = TRUE,
block = FALSE,
mu = 1
)
|
data |
Input matrix of size (p x n) with p < n. |
k |
Number of components, 0 < k < p. |
intervals |
The amount of intervals in the range of values of rho for which gpower is run. For l1, the range of values is [0-1], for l0, the range is [0-0.33]. The block algorithms tend to stop at 0.4 and will only cover the range where gpower is able to run. |
reg |
regularisation type to use in the optimization. Either 'l0' or 'l1'. The default is 'l1' since it performed best in experiments. |
center |
Centers the data. Either TRUE or FALSE. The default is TRUE. |
block |
Optimization method. If FALSE, the components are calculated individually. If TRUE, all components are calculated at the same time. The default is FALSE. |
mu |
Mean to be applied to each component in the block. Either a vector of float of size k or a float which will be repeated k times. Only used if block is TRUE. The default is 1. |
1 2 3 4 5 6 7 8 9 10 11 12 13 |
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