争论点是：用蒙特卡罗模拟法估算积分是否属于“统计学”？类似地，统计力学是否属于统计学？
昨天给过犹他大学的网址：“用随机模拟方法积分”。
至于你现在炒的“蒙法属于统计学”，俺知道你给过心理学硕士论文，现在又给中文垃圾。
对这个方法属于哪个学科有兴趣，者不妨看看下面两个网址。其实这是个简单方法，好比加减法，归属代数、分析都行。
一是美国大学主要的计算软件Matlab官网：
https://www.mathworks.com/matlabcentral/fileexchange/89782-monte-carlo-simulation
“Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution.”
二是《信息系统百科全书》，与英文维基相似，下面是对蒙特卡罗方法（MCM）的解释：
Encyclopedia of Information Systems, 2003
Simulation models can be generally classified into one of three major types, namely, continuous event simulation, discrete event simulation, and Monte Carlo simulation or Monte Carlo methods (MCM). In simple terms, MCM may be any procedure that uses randomly generated numbers to solve a problem. By this definition, any simulation model can be considered as using MCM. Law and Kelton use the term Monte Carlo Method to define a procedure that uses randomly generated variables to solve problems in which the passage of time is not of consequence (i.e., the problem is static in nature). Pritsker (1995) defines the aim of discrete and continuous event simulation as reproducing the activities of the entities in a system over time, to better understand the behavior and performance of a system. We use both these definitions to classify MCM problems as those simulation problems that either do not involve the passage of time and/or do not involve entities and activities.
昨天给过犹他大学的网址：“用随机模拟方法积分”。
至于你现在炒的“蒙法属于统计学”，俺知道你给过心理学硕士论文，现在又给中文垃圾。
对这个方法属于哪个学科有兴趣，者不妨看看下面两个网址。其实这是个简单方法，好比加减法，归属代数、分析都行。
一是美国大学主要的计算软件Matlab官网：
https://www.mathworks.com/matlabcentral/fileexchange/89782-monte-carlo-simulation
“Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution.”
二是《信息系统百科全书》，与英文维基相似，下面是对蒙特卡罗方法（MCM）的解释：
Encyclopedia of Information Systems, 2003
Simulation models can be generally classified into one of three major types, namely, continuous event simulation, discrete event simulation, and Monte Carlo simulation or Monte Carlo methods (MCM). In simple terms, MCM may be any procedure that uses randomly generated numbers to solve a problem. By this definition, any simulation model can be considered as using MCM. Law and Kelton use the term Monte Carlo Method to define a procedure that uses randomly generated variables to solve problems in which the passage of time is not of consequence (i.e., the problem is static in nature). Pritsker (1995) defines the aim of discrete and continuous event simulation as reproducing the activities of the entities in a system over time, to better understand the behavior and performance of a system. We use both these definitions to classify MCM problems as those simulation problems that either do not involve the passage of time and/or do not involve entities and activities.
锟斤拷锟洁辑时锟斤拷: 2023-05-01 11:33:12
