This paper considers simulation model in applied science from a statistical perspective, points out potential statistical pitfalls in calibration, and opportunities for the use of statistical regularities to reduce computational requirements and provide a foundation for systematic testing and evaluation. Sections of the paper deal with the impact of numerical approximation on\ud the statistical properties of estimators, the use of simulation methods to assist statistical inference, and the use of nested multinomial approximations for computational tractability and robustness
The last century has seen a growing interest in complexity in economics and social sciences. The nee...
For decades, introductory statistics has been taught as an application of formulas, making use of no...
This book has a very large scope in that, beyond its title, it covers the dual fields of computation...
This paper considers simulation model in applied science from a statistical perspective, points out...
This paper discusses how the results of simulation models can be made more reliable and the method o...
This paper discusses how the results of simulation models can be made more reliable and the method o...
The purpose of this paper is to provide a step by step computational approach to handle statistical ...
The focus of this thesis is twofold. First, it delivers a new look at existing simulation-based meth...
In this paper, I present a number of leading examples in the empirical literature that use simulatio...
Over the last few years, major advances have occurred in the field of simulation. In partic-ular, Mc...
In this book, we study theoretical and practical aspects of computing methods for mathematical model...
A comprehensive introduction to sampling-based methods in statistical computing The use of computer...
Sampling-based computational methods have become a fundamental part of the numerical toolset of prac...
This chapter is an attempt to answer the question “how many runs of a computational simulation shoul...
A numerical simulation is a computing calculation following a program that develops a mathematical m...
The last century has seen a growing interest in complexity in economics and social sciences. The nee...
For decades, introductory statistics has been taught as an application of formulas, making use of no...
This book has a very large scope in that, beyond its title, it covers the dual fields of computation...
This paper considers simulation model in applied science from a statistical perspective, points out...
This paper discusses how the results of simulation models can be made more reliable and the method o...
This paper discusses how the results of simulation models can be made more reliable and the method o...
The purpose of this paper is to provide a step by step computational approach to handle statistical ...
The focus of this thesis is twofold. First, it delivers a new look at existing simulation-based meth...
In this paper, I present a number of leading examples in the empirical literature that use simulatio...
Over the last few years, major advances have occurred in the field of simulation. In partic-ular, Mc...
In this book, we study theoretical and practical aspects of computing methods for mathematical model...
A comprehensive introduction to sampling-based methods in statistical computing The use of computer...
Sampling-based computational methods have become a fundamental part of the numerical toolset of prac...
This chapter is an attempt to answer the question “how many runs of a computational simulation shoul...
A numerical simulation is a computing calculation following a program that develops a mathematical m...
The last century has seen a growing interest in complexity in economics and social sciences. The nee...
For decades, introductory statistics has been taught as an application of formulas, making use of no...
This book has a very large scope in that, beyond its title, it covers the dual fields of computation...