Add to ORKGBehaviour of the NORTA Method for correlated random vector generation as the dimension increase
This paper considers stochastic simulations with correlated input random variables having NORmal-To-...
This paper considers stochastic simulations with correlated input random variables having NORmal-To-...
This paper considers stochastic simulations with correlated input random variables having NORmal-To-...
The NORTA method for multivariate generation is a fast general purpose method for generating samples...
There is a growing need to capture dependence between random variables that serve as primitive input...
We describe a model for representing random vectors whose component random variables have arbitrary ...
There is a growing need for the ability to model and generate samples of dependent random variables...
Generating multivariate random vectors is a crucial part of the input analysis involved in discrete-...
Growing technology, escalating capability, and increasing complexity in many real world systems dema...
We introduce an approximate variant of the NORTA method which aims at generating structured data fro...
In simulation we often have to generate correlated random variables by giving a reference intercorre...
AbstractWe extend and improve two existing methods of generating random correlation matrices, the on...
Apopular approach for modeling dependence in a finite-dimensional random vector X with given univari...
The simulation of multivariate data is often necessary for assessing the performance of multivariat...
Simulating sample correlation matrices is important in many areas of statistics. Approaches such as ...
This paper considers stochastic simulations with correlated input random variables having NORmal-To-...
This paper considers stochastic simulations with correlated input random variables having NORmal-To-...
This paper considers stochastic simulations with correlated input random variables having NORmal-To-...
The NORTA method for multivariate generation is a fast general purpose method for generating samples...
There is a growing need to capture dependence between random variables that serve as primitive input...
We describe a model for representing random vectors whose component random variables have arbitrary ...
There is a growing need for the ability to model and generate samples of dependent random variables...
Generating multivariate random vectors is a crucial part of the input analysis involved in discrete-...
Growing technology, escalating capability, and increasing complexity in many real world systems dema...
We introduce an approximate variant of the NORTA method which aims at generating structured data fro...
In simulation we often have to generate correlated random variables by giving a reference intercorre...
AbstractWe extend and improve two existing methods of generating random correlation matrices, the on...
Apopular approach for modeling dependence in a finite-dimensional random vector X with given univari...
The simulation of multivariate data is often necessary for assessing the performance of multivariat...
Simulating sample correlation matrices is important in many areas of statistics. Approaches such as ...
This paper considers stochastic simulations with correlated input random variables having NORmal-To-...
This paper considers stochastic simulations with correlated input random variables having NORmal-To-...
This paper considers stochastic simulations with correlated input random variables having NORmal-To-...