Calculating the Shannon entropy for symbolic sequences has been widely considered in
many fields. For descriptive statistical problems such as estimating the N-gram entropy of …

Entropy estimation plays a significant role in biology, economics, physics, communication
engineering and other disciplines. It is increasingly used in software engineering, eg in …

Information theoretic entropy measures are calculated from estimates of the probabilities of
the constituent symbolic events. In natural sequences, such as those occurring in human …

A pragmatic approach for entropy estimation is presented, first for discrete variables, then in
the form of an extension for handling continuous and/or multivariate ones. It is based on …

Entropy estimation faces numerous challenges when applied to various real-world
problems. Our interest is in divergence and entropy estimation algorithms which are capable …

It is well known that to estimate the Shannon entropy for symbolic sequences accurately
requires a large number of samples. When some aspects of the data are known it is …

We are concerned with estimating alphabet size $ N $ from a stream of symbols taken
uniformly at random from that alphabet. We define and analyze a memory-restricted variant …

A very pragmatic approach for measuring memory (or inertia) in dynamic sequences of
symbols (symbol dynamics) is proposed, where only intervals between coincidences of …