
Javier Lara
https://www.simiode.org/members/4412

9005SInvasiveSpeciesModel
08 Aug 2019   Contributor(s):: Eric Stachura
This scenario takes students through the development of an invasive species partial differential equation model. Basic models are discussed first, which lead students to eventually develop their own model which takes into account dispersion. Students will explore various Mathematica modules...

1141SM&MGameRevisited
27 Aug 2018   Contributor(s):: Mehdi HakimHashemi
In this project students will learn to find a probability distribution using the classical M&M game in SIMIODE.

1108SPoissonProcess
27 Aug 2018   Contributor(s):: Mehdi HakimHashemi
In this project students learn to derive the probability density function (pdf) of the Poisson distribution and the cumulative distribution (cdf) of the waiting time. They will use them to solve problems in stochastic processes.

1039SStochasticPopModels
11 Sep 2016   Contributor(s):: Dan Flath
We offer students the opportunity to develop several strategies for creating a population model using some simple probabilistic assumptions. These assumptions lead to a system of differential equations for the probability that a system is in state (or population size) n at time t. We go further...

1001pgfSBirthDeathImmigration
09 Feb 2016   Contributor(s):: Chris McCarthy
We develop a mathematical model of a death and immigration process using m&m's as a stochastic process with the help of probability generating functions.

1027SStochasticProcesses
04 Jun 2015   Contributor(s):: Brian Winkel
We build the infinite set of first order differential equations for modeling a stochastic process, the socalled birth and death equations. We will only need to use integrating factor solution strategy or DSolve in Mathematica for success. We work to build our model of random events which...

7008SMachineReplacement
04 Jun 2015   Contributor(s):: Brian Winkel
Students build an differential equation model using a convolution for machine replacement strategies for two different machine failure models: (1) exponentially distributed failure (student exercise) and (2) fixed time replacement. We discuss all the necessary probability notions which...