Introduction. The mathematical theory of probability is now ordinarily formulated in terms of measure theory. The formalization of a succession of n trials is in terms of ^-dimensional measure ; that of a sequence of trials is in terms of (denumerably) infinite-dimensional measure ; that of a continuous set of trials (a set dependent on a continuous time parameter say) is in terms of measure in...

We report experimental results on the acceleration component probability distribution function at R λ = 690 to probabilities of less than 10 −7. This is an improvement of more than an order of magnitude over past measurements and allows us to conclude that the fourth moment converges and the flatness is approximately 55. We compare our probability distribution to those predicted by several mode...

We show that a simple, general, and easily reproducible method for generating non-uniform sampling (NUS) schedules preserves the benefits of random sampling, including inherently reduced sampling artifacts, while removing the pitfalls associated with choosing an arbitrary seed. Sampling schedules are generated from a discrete cumulative distribution function (CDF) that closely fits the continuo...

We constructed an analog circuit generating fluctuations of which a probability density function has power law tails. In the circuit fluctuations with an arbitrary exponent of the power law can be obtained by tuning the resistance. A theory of a differential equation with both multiplicative and additive noises which describes the circuit is introduced. The circuit is composed of a noise genera...

Suppose that in the four tests Alice’s scores are 90, 95, 85, 90, and Bob’s scores are 85, 95, 90, 90. How to evaluate their scores? In this paper, we introduce the concept of ordered probability mass function which can be used to find a probability mass function with smaller variance. More interestingly, we can use it to distinguish sequences of positive numbers statistically.

The inversion method is an effective approach for transforming uniform random points according to a given probability density function. In two dimensions, horizontal and vertical displacements are computed successively using a marginal and then all conditional density functions. When quasi-random low-discrepancy points are provided as input, spurious artifacts might appear if the density functi...

In this article, a new algorithm generating discrete uniform distribution on n elements from binary random source is proposed by introducing the notion of coprimity and modulo function in number theory. The generalization Von Neumann’s for n=2 [4] Dijkstra’s prime [1]. proof validity introduces variable residual classes, combines ideas techniques both probability theory

Present investigation deals with optimal management policy for Markovian queue with server breakdowns, vacations and setup. The customers arrive in Poisson fashion to get the service. The server may breakdown during the service and goes for repair immediately. By applying probability generating function technique queue length distribution is obtain for different states of the server. Further we...

We analyze and study the performance of amplify-and-forward cooperative diversity communication network with best-relay selection over Weibull fading channel. In this paper, a closed-form expression for the moment generating function (MGF) of the total signal-to-noise ratio at the destination is derived in terms of the tabulated Meijer’s G-function. By the help of this derived MGF expression, w...

We often encounter pairs of variables in the world whose mutual relationship can be described by a function. After training, human responses closely correspond to these functional relationships. Here we study how humans predict unobserved segments of a function that they have been trained on and we compare how human predictions differ to those made by various function-learning models in the lit...