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Since simulation can accommodate complex problems of this sort, it is often used in analysing real options [1] where management's decision at any point is a function of multiple underlying variables. Simulation can similarly be used to value options where the payoff depends on the value of multiple underlying assets [ 8 ] such as a Basket ...
In contrast, the Gillespie algorithm allows a discrete and stochastic simulation of a system with few reactants because every reaction is explicitly simulated. A trajectory corresponding to a single Gillespie simulation represents an exact sample from the probability mass function that is the solution of the master equation.
The first applications of computer simulations for dynamic systems was in the aerospace industry. [5] Commercial uses of dynamic simulation are many and range from nuclear power, steam turbines, 6 degrees of freedom vehicle modeling, electric motors, econometric models, biological systems, robot arms, mass-spring-damper systems, hydraulic systems, and drug dose migration through the human body ...
The density function of the t-distribution is given by the following equation: [4] = (+) (+) +, where is the number of degrees of freedom and is the gamma function. For large values of n , the t-distribution doesn't significantly differ from a standard normal distribution .
Anyway, using the homotopy analysis method or harmonic balance, one can derive a frequency response equation in the following form: [9] [5] [() + ()] =. For the parameters of the Duffing equation, the above algebraic equation gives the steady state oscillation amplitude z {\displaystyle z} at a given excitation frequency.
In a mathematical programming model, if the objective functions and constraints are represented entirely by linear equations, then the model is regarded as a linear model. If one or more of the objective functions or constraints are represented with a nonlinear equation, then the model is known as a nonlinear model.
The simultaneous equation model requires a theory of reciprocal causality that includes special features if the causal effects are to be estimated as simultaneous feedback as opposed to one-sided 'blocks' of an equation where a researcher is interested in the causal effect of X on Y while holding the causal effect of Y on X constant, or when ...
For the Wiener process the drift term is constant, whereas for the Ornstein–Uhlenbeck process it is dependent on the current value of the process: if the current value of the process is less than the (long-term) mean, the drift will be positive; if the current value of the process is greater than the (long-term) mean, the drift will be negative.