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	== '''Stochastic Model''' ==		== '''Stochastic Model''' ==
		+	Stochastic methods
		+	Now we are going to explain to you how we implement the Gilliespie method to introduce stochasticity to our math model.
		+	The complete method consists of eight steps.
		+	#Define the number of cells.
		+	#Define the time of the simulation
		+	#Define and name all the constants involved.
		+	#Define creation and destruction expression for each substance involved.
		+	#Apply Gilliespie algorithm.
		+	##Calculate the sample space of the analysed system.
		+
		+	##Calculate time distribution that depends on a random number between 0 and 1.
		+
		+	##Generate ranges for the space created in the step 5.a, taking into account the random number from step 5.b. After that, assign an answer to each range.
		+	#Take the outputs from the simulation and convert them into regular interval vectors.
		+	#Obtain the Gilliespie function mean values.
		+	#Plot the obtained functions.

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Revision as of 02:23, 17 September 2012

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Stochastic Model

Stochastic methods Now we are going to explain to you how we implement the Gilliespie method to introduce stochasticity to our math model. The complete method consists of eight steps.

1. Define the number of cells.
2. Define the time of the simulation
3. Define and name all the constants involved.
4. Define creation and destruction expression for each substance involved.
5. Apply Gilliespie algorithm.
   1. Calculate the sample space of the analysed system.

1. 1. Calculate time distribution that depends on a random number between 0 and 1.

1. 1. Generate ranges for the space created in the step 5.a, taking into account the random number from step 5.b. After that, assign an answer to each range.
2. Take the outputs from the simulation and convert them into regular interval vectors.
3. Obtain the Gilliespie function mean values.
4. Plot the obtained functions.