If T is a stopping time on a martingale {St }, the mth order moments of T and ST (for integers m ≧ 2) are related by an identity known as a Wald equation of order m. Wald equations hold under certain conditions, which are simplified in this paper by showing that among the set of previously known conditions, some are implied by the others.

In a series of papers Whittle has proposed locating the optimal boundary between the continuation region and the stopping region, in the no-overshoot approximation, for a class of sequential analysis problems by using the criterion that the gradient of the objective function must be continuous at the boundary. It is shown here that the result originally proposed by Whittle is not true in the generality which he supposed, and an indication is given of some of the circumstances in which it does hold.

The coefficients of variation and serial correlation are given for the inter-event intervals of the process obtained by selecting every kth event of the pooled output of several periodic point processes. Relevance to physiological research is explained.

Sharma and Autar [6] have formed a functional equation in two variables containing two parameters which, as a particular case, includes Daróczy's [1] generalized functional equation used in information theory. The solutions of our functional equation, under suitable boundary conditions, lead to an inaccuracy function of a new type. A characterization of this inaccuracy function and the convexity of Daróczy's entropy of type-ß have been given in this paper.

In this paper the minimum discrimination information estimate is used to compute the log-likelihood ratio or logarithm of the Radon-Nikodym derivative In (dP 1/dP 2) when the stochastic process {x(t), t∈T) has either the probability measure P 1 or P 2. One example tests the mean value function of Gaussian processes. The other tests the mean value function of a continuous time Poisson process.

Realizations of the autoregressive series considered by Kendall are generated using both Gaussian and uniformly distributed random variables. Estimates of the autocorrelation and power spectrum of the process obtained from these realizations are compared with the theoretical expressions derived by Bartlett. Agreement is well within the theoretical variance.

Let Dj be a domain in nj ,-dimensional Euclidean space, for j = 1, …, k. Suppose that for each j = 1,…, k, Nj points are chosen independently at random in Dj. A theorem, which is an extension of a theorem of Crofton, is proved about the expected value of functions of the points.

The distribution of the volume occupied by random spheres in a cube is considered, both when the number of spheres is fixed and when their centres form a Poisson field. The mean and variance are obtained and in the latter case the distribution is proved to converge to normality. The probability of complete coverage is also obtained heuristically.