We explore model based techniques of phylogenetic tree inference exercising Markov invariants. Markov invariants are group invariant polynomials and are distinct from what is known in the literature as phylogenetic invariants, although we establish a commonality in some special cases. We show that the simplest Markov invariant forms the foundation of the Log-Det distance measure. We take as our...

A web prediction model helps to predict user requests ahead of time, making web servers more responsive. Several prediction techniques have been tried in the past; Markov based prediction models being the most popular ones. Among these, the All-K-order Markov model has been found to be most effective. We designed a Markov tree, which is a fourth order model but behaves like an All-K-order Marko...

Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corres...

Packet losses are commonplace over the Internet, and can severely affect the quality of delay sensitive multimedia applications. In the current Internet architecture it is up to the application to react to the perceived congestion level in the network. The ability of the application to react is enhanced by the availability of simple and efficient loss models. Traditionally, Markov chain models ...

We explore model-based techniques of phylogenetic tree inference exercising Markov invariants. Markov invariants are group invariant polynomials and are distinct from what is known in the literature as phylogenetic invariants, although we establish a commonality in some special cases. We show that the simplest Markov invariant forms the foundation of the Log-Det distance measure. We take as our...