Volume 35 - Issue 2 - December 2010

Time series analysis to forecast temperature change
   Tanja Van Hecke
   pp. 6369
  
  
Abstract
ARIMA models are often used to model the evolution in time of economic issues. We demonstrate that an ARIMA model is also valuable in the environmental field, where the evolution of climate change is causing many concerns. Can we confirm global warming by mathematical prediction theories?

A predator–prey model with spiteful hawk–dove predators
   Noelle Sio, Jennifer Switkes
   pp. 7082
  
  
Abstract
In this paper, we focus on predator behavior in a predator–prey model. We assume that the predator–prey interactions take place on a slow time scale in comparison to predator behavioral dynamics, with the prey model equation taking a classic Lotka–Volterra form. Using replicator equations, we couple fast time scale classical hawk–dove predator dynamics with spiteful predation, that is, with predators willing to harm themselves in order to harm their counterparts even more. By assuming a mixture of spiteful and nonspiteful individuals, we observe the bifurcation effects of various proportions of spiteful individuals.

Random processes, social groups, and households
   C. W. Lloyd-Smith, V. E. Jennings
   pp. 8395
  
  
Abstract
This paper uses random processes to develop mathematical models of size distributions for families and households. Some links are given to ideas in Cohen (1972) on social groups of primates, and with Goodman et al. (1974), (1975) on family formation. Little's law from queueing theory yields relationships between relevant populations, birth rates, life expectancy, and other demographic variables. The superposition of point processes arising from these demographic variables generates Poisson inputs, each of which is associated with a family or household. Under steady state conditions, truncated Poisson distributions are found for household and family size. Numerical results are provided.

A generalization of the vernier algorithm
   Rabe-R. von Randow
   pp. 96100
  
  
Abstract
After a short description of the vernier and brief biographies of the two scientists connected with it, we present an algorithm which generalizes the vernier algorithm and has a number of new and surprising properties not possessed by the vernier algorithm.

Collision of one-dimensional random walks
   David K. Neal
   pp. 101110
  
  
Abstract
Let X and Y be simple random walks with initial heights jX and jY, where jX < jY and jYjX is even. The processes independently move upward or downward one unit at a time on each simultaneous step with the probability of X moving upward being pX and the probability of Y moving upward being pY. We give the condition for which paths almost surely attain the same height, and for this condition we derive the average number of steps needed for paths to collide at the same height and the average height at the time of collision.

Gambler's ruin? Some aspects of coin tossing
   Porter W. Johnson, David Atkinson
   pp. 111121
  
  
Abstract
What is the average number of coin tosses needed before a particular sequence of heads and tails first turns up? This problem is solved in our paper, starting with doubles; a tail, followed by a head, turns up on average after only four tosses, while six tosses are needed for two successive heads. The method is extended to encompass the triples head-tail-tail and head-head-tail, but head-tail-head and head-head-head are surprisingly more recalcitrant. However, the general case is finally solved by using a new algorithm, even for relatively long strings. It is shown that the average number of tosses is always an even integer.

The perimeter of an ellipse
   Tirupathi R. Chandrupatla, Thomas J. Osler
   pp. 122131
  
  
Abstract
There is no simple way to calculate the perimeter of an ellipse. In this expository paper we review and compare four methods of evaluating this perimeter. These methods are known by the names Maclaurin, Gauss–Kummer, Cayley, and Euler. Maclaurin's method is derived in detail, while the other three are simply described. A short introduction to hypergeometric functions is included, since these functions are useful for finding the elliptic perimeter. We compare the usefulness of these four calculations, An appendix gives MICROSOFT EXCEL® programs for computing the perimeter.

Letter to the Editor: The inverse law of large numbers
   Oscar Sheynin
   pp. 132133
  

Index to Volume 35
   p. 134