ot_indices_wb {gsaot} | R Documentation |
Estimate Wasserstein-Bures approximation of the optimal transport solution
Description
Estimate Wasserstein-Bures approximation of the optimal transport solution
Usage
ot_indices_wb(
x,
y,
M,
boot = FALSE,
R = NULL,
parallel = "no",
ncpus = 1,
conf = 0.95,
type = "norm"
)
Arguments
x |
A matrix or data.frame containing the input(s) values. The values
can be numeric, factors, or strings. The type of data changes the
partitioning. If the values are continuous (double), the function
partitions the data into |
y |
A matrix containing the output values. Each column represents a different output variable, and each row represents a different observation. Only numeric values are allowed. |
M |
A scalar representing the number of partitions for continuous inputs. |
boot |
(default |
R |
(default |
parallel |
(default |
ncpus |
(default |
conf |
(default |
type |
(default |
Value
A gsaot_indices
object containing:
-
method
: a string that identifies the type of indices computed. -
indices
: a names array containing the sensitivity indices between 0 and 1 for each column in x, indicating the influence of each input variable on the output variables. -
bound
: a double representing the upper bound of the separation measure or an array representing the mean of the separation for each input according to the bootstrap replicas. -
x
,y
: input and output data provided as arguments of the function. -
inner_statistic
: a list of matrices containing the values of the inner statistics for the partitions defined bypartitions
. Ifmethod = wasserstein-bures
, each matrix has three rows containing the Wasserstein-Bures indices, the Advective, and the Diffusive components. -
partitions
: a matrix containing the partitions built to calculate the sensitivity indices. Each column contains the partition associated to the same column inx
.
If boot = TRUE
, the object contains also:
-
indices_ci
: adata.frame
with first column the input, second and third columns the lower and upper bound of the confidence interval. -
inner_statistic_ci
: a list of matrices. Each element of the list contains the lower and upper confidence bounds for the partition defined by the row. -
bound_ci
: a list containing the lower and upper bounds of the confidence intervals of the separation measure bound. -
type
,conf
: type of confidence interval and confidence level, provided as arguments. -
W_boot
: list of bootstrap objects, one for each input.
See Also
Examples
N <- 1000
mx <- c(1, 1, 1)
Sigmax <- matrix(data = c(1, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 1), nrow = 3)
x1 <- rnorm(N)
x2 <- rnorm(N)
x3 <- rnorm(N)
x <- cbind(x1, x2, x3)
x <- mx + x %*% chol(Sigmax)
A <- matrix(data = c(4, -2, 1, 2, 5, -1), nrow = 2, byrow = TRUE)
y <- t(A %*% t(x))
x <- data.frame(x)
y <- y
ot_indices_wb(x, y, 10)