Public
Edited
Mar 25, 2023
1 fork
numberOfTrajectories = Math.floor(maxSteps / period)
noiseFunction = d3.randomNormal(0, sigma)
growthRate = mu - (sigma * sigma) / 2
simulatedTrajectories = {
// Initialise an array of runs
const data = []
// For each run…
for( let r = 0; r < numberOfTrajectories; r++){
// Determine the starting point of the run in the data array so each run is added consecutively in the array.
const startingArrayPos = (r * period)
// Initialise the start of each run with the initialValue and reset the timeStep to 0
data[startingArrayPos] = {timeStep: 0, value: initialValue, run: r}
// Step through each timeStep
for(let t = 1; t < period; t++){
// Determine the previous value, which will be the value of the immediately preceeding timeStep
const previousValue = data[startingArrayPos+t-1]['value']
// Calculate the new value, by multiplying the previous value by mu + a sample from the noise function.
const newValue = previousValue * (mu + noiseFunction())
data[startingArrayPos+t] = {timeStep: t, value: newValue, run: r}
}
}
return data
}
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