Description Usage Arguments Details Value Slots See Also Examples
Holds the information about how the sigma
parameter for a DiffusionMap was obtained,
and in this way provides a plotting function for the find_sigmas heuristic.
You should not need to create a Sigmas object yourself. Provide sigma
to DiffusionMap instead or use find_sigmas.
1 2 3 4 5 6 7 8 9 10 | Sigmas(...)
## S4 method for signature 'Sigmas'
optimal_sigma(object)
## S4 method for signature 'Sigmas'
print(x)
## S4 method for signature 'Sigmas'
show(object)
|
object, x |
Sigmas object |
... |
See “Slots” below |
A Sigmas object is either created by find_sigmas or by specifying the sigma
parameter to DiffusionMap.
In the second case, if the sigma
parameter is just a number,
the resulting Sigmas
object has all slots except of optimal_sigma
set to NULL
.
Sigmas
creates an object of the same class
optimal_sigma
retrieves the numeric value of the optimal sigma or local sigmas
log_sigmas
Vector of length m containing the \log_{10} of the σs
dim_norms
Vector of length m-1 containing the average dimensionality \langle p \rangle for the respective kernel widths
optimal_sigma
Multiple local sigmas or the mean of the two global σs around the highest \langle p \rangle (c(optimal_idx, optimal_idx+1L)
)
optimal_idx
The index of the highest \langle p \rangle.
avrd_norms
Vector of length m containing the average dimensionality for the corresponding sigma.
find_sigmas
, the function to determine a locally optimal sigma and returning this class
1 2 3 4 | data(guo)
sigs <- find_sigmas(guo, verbose = FALSE)
optimal_sigma(sigs)
print(sigs)
|
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