Odefy -- From discrete to continuous models

From Discrete to Continuous Gene Regulation Models – A Tutorial Using the Odefy Toolbox

From Discrete to Continuous

From a development of an original idea due to Schwinger, it is shown that it is possible to recover, from the quantum description of a degree of freedom characterized by a finite number of states (i.e., without classical counterpart) the usual canonical variables of position/momentum and angle/angular momentum .

A continuous approximation fitting to the discrete distributions using ODE

The probability density functions fitting to the discrete probability functions has always been needed, and very important. This paper is fitting the continuous curves which are probability density functions to the binomial probability functions, negative binomial geometrics, poisson and hypergeometric. The main key in these fittings is the use of the derivative concept and common differential ...

Discrete versus continuous models in evolutionary dynamics: From simple to simpler-and even simpler-models

There are many different models—both continuous and discrete— used to describe gene mutation fixation. In particular, the Moran process, the Kimura equation and the replicator dynamics are all well known models, that might lead to different conclusions. We present a discussion of a unified framework to embrace all these models, in the large population regime.

From Discrete-Time Models to Continuous-Time, Asynchronous Models of Financial Markets

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