vars_to | R Documentation |
It computes VARS-TO following \insertCiteRazavi2016a;textualsensobol.
vars_to(Y, star.centers, params, h, method = "all.step")
Y |
A numeric vector with the model output obtained from the matrix created with
|
star.centers |
Positive integer, number of star centers. |
params |
Character vector with the name of the model inputs. |
h |
Distance between pairs. |
method |
Type of computation. If |
VARS is based on variogram analysis to characterize the spatial structure and variability
of a given model output across the input space \insertCiteRazavi2016asensobol. Variance-
based total-order effects can be computed as by-products of the VARS framework. The total-order index
is related to the variogram \gamma(.)
and co-variogram C(.)
functions by the
following equation:
T_i = \frac{\gamma (h_i) + E \left [C_{\mathbf{x}_{\sim i}} (h_i) \right]}{\hat{V}(y)}
where x^*_{\sim i}
is a vector of all k
factors except x_i
.
A data.table
with the VARS-TO indices of each parameter.
# Define settings
star.centers <- 10; params <- paste("X", 1:3, sep = ""); h <- 0.1
# Create STAR-VARS
mat <- vars_matrices(star.centers = star.centers, params = params, h = h)
# Run model
y <- sensobol::ishigami_Fun(mat)
# Compute VARS-TO
ind <- vars_to(Y = y, star.centers = star.centers, params = params, h = h)
ind
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