Add to ORKGSTOLOFF (1968) presented a general method using a digital computer to generate random numbers having various specified distributions. Like most general methods it is not efficient when used for the particular case. His method is essentially that used for Monte Carlo integration of a function and is described by Moshman (1967). The specified density is inscribed in a rectangle of width x and height y. One could estimate the percentage of the total area, xy, under the density by generating random coordinates (ij) and counting the number falling below the inscribed curve. Stoloff’s method is in-verse integration in that a random coordinate is generated and if it falls below the curve, then the x-coordinate is used as a random deviate having th...
his paper will trace the history and development of a useful stochastic method for approximating cer...
Practical methods for generating acceptable random numbers from a variety of probability distributio...
This chapter covers the basic design principles and methods for uniform random number generators use...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
We suggest an interesting and fast method for generating normal, exponential, t, von Mises, and cert...
The cutting corners algorithm can be used to generate random numbers from any unimodal density which...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
In order to carry out the simulation, we need a source of random numbers distributed according to th...
In order to carry out the simulation, we need a source of random numbers distributed according to th...
To observe values of a random variable that follows some arbitrary distribution, it is only necessar...
To observe values of a random variable that follows some arbitrary distribution, it is only necessar...
Methods are developed, and Fortran 63 CODAP computer programs are demonstrated, to generate random ...
Work has been done in generating random variates of some distributions for simulation purposes. A su...
his paper will trace the history and development of a useful stochastic method for approximating cer...
Practical methods for generating acceptable random numbers from a variety of probability distributio...
This chapter covers the basic design principles and methods for uniform random number generators use...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
We suggest an interesting and fast method for generating normal, exponential, t, von Mises, and cert...
The cutting corners algorithm can be used to generate random numbers from any unimodal density which...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
In order to carry out the simulation, we need a source of random numbers distributed according to th...
In order to carry out the simulation, we need a source of random numbers distributed according to th...
To observe values of a random variable that follows some arbitrary distribution, it is only necessar...
To observe values of a random variable that follows some arbitrary distribution, it is only necessar...
Methods are developed, and Fortran 63 CODAP computer programs are demonstrated, to generate random ...
Work has been done in generating random variates of some distributions for simulation purposes. A su...
his paper will trace the history and development of a useful stochastic method for approximating cer...
Practical methods for generating acceptable random numbers from a variety of probability distributio...
This chapter covers the basic design principles and methods for uniform random number generators use...