Add to ORKGStatistical emulation is a technique for studying the behavior of computational simulation models. With this approach, a statistical function is fitted to the observed relations between model inputs and outputs based on systematic experimentation with the simulation model. The resulting function provides information about the general behavior of the simulation model and can be used, for example, for model simplification, optimization, and calibration. In this article, we discuss the general principles of statistical emulation, introduce readers to regression metamodels and Gaussian process emulators as two examples of commonly used statistical functions, and point readers to experimental designs that can be used for fitting these types of f...
Statistical emulators for the outputs of complex computer codes (simulators) are typically construct...
Modeling and simulation techniques have demonstrated success in studying biological systems. As the ...
Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistic...
Statistical emulation is a technique for studying the behavior of computational simulation models. W...
The article describes a new methodology for the emulation of high-order, dynamic simulation models. ...
This introductory tutorial gives a survey on the use of statistical designs for what if-or sensitivi...
We introduce statistical techniques required to handle complex computer models with potential applic...
Numerical simulation codes are very common tools to study complex phenomena, but they are often time...
ABSTRACT. This paper compares two strategies that reduce the cost of running a simulator of the freq...
Many scientific systems are studied using computer codes that simulate the phenomena of interest. Co...
Emulator technology is the methodology that replaces simulators in engineering design by surrogate m...
Scientific investigations are often expensive and the ability to quickly perform analysis of data on...
In practice, simulation analysts often change only one factor at a time, and use graphical analysis ...
Computer models or simulators are becoming increasingly common in many fields in science and enginee...
Computer models, or simulators, are widely used in a range of scientific fields to aid understanding...
Statistical emulators for the outputs of complex computer codes (simulators) are typically construct...
Modeling and simulation techniques have demonstrated success in studying biological systems. As the ...
Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistic...
Statistical emulation is a technique for studying the behavior of computational simulation models. W...
The article describes a new methodology for the emulation of high-order, dynamic simulation models. ...
This introductory tutorial gives a survey on the use of statistical designs for what if-or sensitivi...
We introduce statistical techniques required to handle complex computer models with potential applic...
Numerical simulation codes are very common tools to study complex phenomena, but they are often time...
ABSTRACT. This paper compares two strategies that reduce the cost of running a simulator of the freq...
Many scientific systems are studied using computer codes that simulate the phenomena of interest. Co...
Emulator technology is the methodology that replaces simulators in engineering design by surrogate m...
Scientific investigations are often expensive and the ability to quickly perform analysis of data on...
In practice, simulation analysts often change only one factor at a time, and use graphical analysis ...
Computer models or simulators are becoming increasingly common in many fields in science and enginee...
Computer models, or simulators, are widely used in a range of scientific fields to aid understanding...
Statistical emulators for the outputs of complex computer codes (simulators) are typically construct...
Modeling and simulation techniques have demonstrated success in studying biological systems. As the ...
Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistic...