View source: R/derivative_functions.R
directional_deriv | R Documentation |
Find the (uncertainty modified) inner product between the derivative at a point x
and a proposed direction v
.
directional_deriv(em, x, v, sd = NULL, ...)
em |
The emulator in question |
x |
The point in input space to evaluate at |
v |
The direction to assess |
sd |
How many standard deviations to consider. |
... |
Additional arguments to pass through (eg local.var to the emulator functions) |
Given a point x
and a direction v
, we find the overlap between E[f'(x)] and
v
. The emulated derivative has uncertainty associated with it: the variance is taken
into account using v^{T} Var[f'(x)] v
.
If sd == NULL
, then only the (normed) overlap between the derivative and the direction
vector is returned. Otherwise a pair of values are returned: these are the normed overlap plus
or minus sd
times the uncertainty.
This function is concerned with ascertaining whether a direction is oriented in the direction of the emulator gradient, subject to the uncertainty around the estimate of the derivative. It allows for a consideration of "emulated gradient descent".
Either a single numeric or a pair of numerics (see description)
directional_deriv(SIREmulators$ems[[1]], SIRSample$validation[1,], c(1,1,1))
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