Monte Carlo Simulation of Correlated Random Variables
نویسنده
چکیده
This paper describes a method for the Monte Carlo simulation of two correlated random variables. The author analyses linear combinations of stochastically independent random variables that are equally distributed over the interval (0; 1) (\random numbers") and also examines their distribution. If a suitable matrix of coeecients is chosen, the subsequent transformation results in random variables with the desired distribution properties and the given covariance. The method is carried out for a series of covariances using two exponentially distributed random variables.
منابع مشابه
The Monte Carlo Framework and Financial Applications
In these notes we describe the general Monte-Carlo framework for estimating expectations. We also give several applications from finance and describe how to simulate correlated normal random variables using the Cholesky decomposition of the covariance matrix. The ability to generate correlated normal random variables finds applications throughout finance. These applications include simulating c...
متن کاملUncertainty Modeling
Panchalingam, Geethanjali. Ph.D., Purdue University, May 1992. Uncertainty Modeling of Many Correlated and Skewed Random Variables. Major Professor: Milton E. Harr. This thesis presents a point estimate methodology directly suited to uncertainty modeling for systems with many correlated and skewed random variables. The methodology proposes two models. The models provide a simple but powerful pr...
متن کاملProbabilistic load flow with correlated input random variables using uniform design sampling
This paper proposes a probabilistic load flow (PLF) methodology using uniform design sampling (UDS). The correlation between input random variables has been taken into consideration. The random numbers of random variables uniformly distributed in (0,1) are generated by UDS, and subsequently converted into random numbers of input random variables with desired marginal distributions by marginal t...
متن کاملCorrelated Random Variables in Probabilistic Simulation
A new efficient technique to impose the statistical correlation when using Monte Carlo type method for statistical analysis of computational problems is proposed. The technique is based on stochastic optimization method called Simulated Annealing. The comparison with other techniques presently used and intensive numerical testing showed the superiority and robustness of the method. No significa...
متن کاملBeta - Binomial and Ordinal Joint Model with Random Effects for Analyzing Mixed Longitudinal Responses
The analysis of discrete mixed responses is an important statistical issue in various sciences. Ordinal and overdispersed binomial variables are discrete. Overdispersed binomial data are a sum of correlated Bernoulli experiments with equal success probabilities. In this paper, a joint model with random effects is proposed for analyzing mixed overdispersed binomial and ordinal longitudinal respo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1997