| Type: | Package |
| Title: | Nonparametric Sobol Estimator with Bootstrap Bandwidth |
| Version: | 0.1.0 |
| Author: | Maikol Solís <maikol.solis@ucr.ac.cr> |
| Maintainer: | Maikol Solís <maikol.solis@ucr.ac.cr> |
| Description: | Algorithm to estimate the Sobol indices using a non-parametric fit of the regression curve. The bandwidth is estimated using bootstrap to reduce the finite-sample bias. The package is based on the paper Solís, M. (2018) <doi:10.48550/arXiv.1803.03333>. |
| License: | MIT + file LICENSE |
| URL: | https://github.com/maikol-solis/sobolnp/ |
| BugReports: | https://github.com/maikol-solis/sobolnp/issues |
| Imports: | np, minqa, pbmcapply |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 6.1.1 |
| NeedsCompilation: | no |
| Packaged: | 2019-04-24 12:47:02 UTC; maikol |
| Repository: | CRAN |
| Date/Publication: | 2019-04-29 08:40:02 UTC |
Plot method for objects sobolnp
Description
Plot the Sobol indices based in a non-parametric regression with cross-validation and bootstrap bandwidth
Usage
plot(snp, ...)
## S3 method for class 'sobolnp'
plot(snp, ...)
Arguments
snp |
an object of class |
... |
further arguments passed to the |
Value
A formatted table with the results of the sobolnp
function.
Examples
ishigami.fun <- function(X) {
A <- 7
B <- 0.1
sin(X[, 1]) + A * sin(X[, 2])^2 + B * X[, 3]^4 * sin(X[, 1])
}
X <- matrix(runif(3*100, -pi, pi), ncol = 3)
Y <- ishigami.fun(X)
estimation <- sobolnp(Y = Y, X = X, nboot = 5)
plot(estimation)
Print method for objects sobolnp
Description
Print method for objects sobolnp
Usage
print(snp, ...)
## S3 method for class 'sobolnp'
print(snp, ...)
Arguments
snp |
an object of class |
... |
further arguments passed to the |
Value
A formatted table with the results of the sobolnp
function.
Examples
ishigami.fun <- function(X) {
A <- 7
B <- 0.1
sin(X[, 1]) + A * sin(X[, 2])^2 + B * X[, 3]^4 * sin(X[, 1])
}
X <- matrix(runif(3*100, -pi, pi), ncol = 3)
Y <- ishigami.fun(X)
estimation <- sobolnp(Y = Y, X = X, nboot = 5)
print(estimation)
Nonparametric Sobol Estimator with Bootstrap Bandwidth
Description
Algorithm to estimate the Sobol indices using a non-parametric fit of the regression curve. The bandwidth is estimated using bootstrap to reduce the finite-sample bias.
Usage
sobolnp(Y, X, bandwidth = NULL, bandwidth.compute = TRUE,
bootstrap = TRUE, nboot = 100, ckerorder = 2, mc.cores = 1)
Arguments
Y |
Response continuous variable |
X |
Matrix of independent variables |
bandwidth |
If |
bandwidth.compute |
Logical value. Indicates if the bandwidth should be estimated or not. Defaults to |
bootstrap |
Logical value. Indicates if the estimation should be with bootstrap or not. Defaults to |
nboot |
Number of bootstrap samples taken for the method. Ignored if 'bootstrap = FALSE'. Defaults to |
ckerorder |
Numeric value specifying kernel order (should be one of
|
mc.cores |
Number of cores used. Defaults to |
Value
A list of class sobolnp with the following elements:
- S
First order Sobol indices estimated with nonparametric regression and a cross-validation bandwidth
- bws
Bandwidth estimated with cross-validation
- Sboot
First order Sobol indices estimated with nonparametric regression and a bootstrap bandwidth
- bwsboot
Bandwidth estimated with bootstrap
References
Solís, Maikol. "Nonparametric estimation of the first order Sobol indices with bootstrap bandwidth." arXiv preprint arXiv:1803.03333 (2018).
Examples
ishigami.fun <- function(X) {
A <- 7
B <- 0.1
sin(X[, 1]) + A * sin(X[, 2])^2 + B * X[, 3]^4 * sin(X[, 1])
}
X <- matrix(runif(3*100, -pi, pi), ncol = 3)
Y <- ishigami.fun(X)
estimation <- sobolnp(Y = Y, X = X, nboot = 5)