dot-brownianBridgeEmpcdf: Compute value of the asymptotic CDF occuring in the...
In goncalves-lab/waddR: Statistical tests for detecting differential distributions based on the 2-Wasserstein distance
.brownianBridgeEmpcdf R Documentation
Compute value of the asymptotic CDF occuring in the asymptotic theory-based test
Description
Computes the values of the cumulative distribution function (CDF) of the integral over the squared standard Brownian bridge in the unit interval, where the computation is based on Monte Carlo simulations.
This CDF occurs as an asymptotic distribution in the asymptotic theory-based test using the 2-Wasserstein distance, see Schefzik et al. (2020) for details.
It is used to determine the corresponding p-values in the function .wassersteinTestAsy.
Usage
.brownianBridgeEmpcdf(v)
Arguments
v
a number
Value
Value at v of the asymptotic CDF
References
Schefzik, R., Flesch, J., and Goncalves, A. (2020). waddR: Using the 2-Wasserstein distance to identify differences between distributions in two-sample testing, with application to single-cell RNA-sequencing data.
goncalves-lab/waddR documentation built on June 29, 2023, 12:18 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| .brownianBridgeEmpcdf | R Documentation |
Compute value of the asymptotic CDF occuring in the asymptotic theory-based test
Description
Computes the values of the cumulative distribution function (CDF) of the integral over the squared standard Brownian bridge in the unit interval, where the computation is based on Monte Carlo simulations.
This CDF occurs as an asymptotic distribution in the asymptotic theory-based test using the 2-Wasserstein distance, see Schefzik et al. (2020) for details.
It is used to determine the corresponding p-values in the function .wassersteinTestAsy.
Usage
.brownianBridgeEmpcdf(v)
Arguments
v |
a number |
Value
Value at v of the asymptotic CDF
References
Schefzik, R., Flesch, J., and Goncalves, A. (2020). waddR: Using the 2-Wasserstein distance to identify differences between distributions in two-sample testing, with application to single-cell RNA-sequencing data.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.