Transfer Theorems and Asymptotic Distributional Results for m-ary Search Trees

We derive asymptotics of moments and identify limiting distributions, under the random permutation model on m-ary search trees, for functionals that satisfy recurrence relations of a simple additive form. Many important functionals including the space requirement, internal path length, and the so-called shape functional fall under this framework. The approach is based on establishing transfer theorems that link the order of growth of the input into a particular (deterministic) recurrence to the order of growth of the output. The transfer theorems are used in conjunction with the method of moments to establish limit laws. It is shown that (i) for small toll sequences $(t_n)$ [roughly, $t_n =O(n^{1 / 2})$] we have asymptotic normality if $m \leq 26$ and typically periodic behavior if $m \geq 27$; (ii) for moderate toll sequences [roughly, $t_n = \omega(n^{1 / 2})$ but $t_n = o(n)$] we have convergence to non-normal distributions if $m \leq m_0$ (where $m_0 \geq 26$) and typically periodic behavior if $m \geq m_0 + 1$; and (iii) for large toll sequences [roughly, $t_n = \omega(n)$] we have convergence to non-normal distributions for all values of m.Comment: 35 pages, 1 figure. Version 2 consists of expansion and rearragement of the introductory material to aid exposition and the shortening of Appendices A and B.

A learning design toolkit to create pedagogically effective learning activities

Despite the plethora of Information and Communication Technologies (ICT) tools and resources available, practitioners are still not making effective use of e-learning to enrich the student experience. This article describes a learning design toolkit which guides practitioners through the process of creating pedagogically informed learning activities which make effective use of appropriate tools and resources. This work is part of a digital libraries project in which teaching staff at two universities in the UK and two in the USA are collaborating to share e-learning resources in the subject domains of Physical, Environmental and Human Geography. Finding, or creating, suitable e-learning resources and embedding them in well designed learning activities can be both challenging and time consuming. Sharing and adapting effective designs and solutions is both a stimulant and a time saver. This article describes the background to the specification of a learning activities design toolkit to support teachers as they create or adapt e-learning activities. This uses a model of pedagogical approaches as a basis for developing effective learning design plans and illustrates its use. The authors share their definition of a learning activity and taxonomies for the constituent elements. Real examples are discussed to illustrate their approach

Strong Stationary Duality for Diffusion Processes

We develop the theory of strong stationary duality for diffusion processes on compact intervals. We analytically derive the generator and boundary behavior of the dual process and recover a central tenet of the classical Markov chain theory in the diffusion setting by linking the separation distance in the primal diffusion to the absorption time in the dual diffusion. We also exhibit our strong stationary dual as the natural limiting process of the strong stationary dual sequence of a well chosen sequence of approximating birth-and-death Markov chains, allowing for simultaneous numerical simulations of our primal and dual diffusion processes. Lastly, we show how our new definition of diffusion duality allows the spectral theory of cutoff phenomena to extend naturally from birth-and-death Markov chains to the present diffusion context.Comment: 34 page

The limiting distribution for the number of symbol comparisons used by QuickSort is nondegenerate (extended abstract)

In a continuous-time setting, Fill (2010) proved, for a large class of probabilistic sources, that the number of symbol comparisons used by QuickSort, when centered by subtracting the mean and scaled by dividing by time, has a limiting distribution, but proved little about that limiting random variable Y -- not even that it is nondegenerate. We establish the nondegeneracy of Y. The proof is perhaps surprisingly difficult