Finding Area Under Curve with Stochastic Model

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In summary, the conversation discusses methods for finding the area under an exponential function graph. These methods include an empirical model, finite element model, and a possible stochastic or probability model. The speaker is in search of a formula or set of steps for this model, not a tool like a planimeter. Other potential methods mentioned are Rhomberg, adaptive quadrature, and Gauss-Legendre.
  • #1
kieran1black2
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I have an exponential function graph that was given to me as a question i had to find the points and find three different ways of finding the area under the curve.

I found an Empirical model (finding the formula and integrating from one point to another)

I found a Finite Element model (either using simpson's rule or the trapezoidal rule)

But there seems to be another one called a Stochastic model or probability model.

My question is is there anyone that knows where to find this on the net or knows of it right off the back? I would like to know just the rule or steps and i will do the work myself... thanks
 
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  • #2
You get some device called a planimeter that is (was) used to determine the area under a graph, or the area of any flat surface.
 
  • #3
but that has nothing to do with the stochastic model or probability model...

i need a formula or set of steps not a tool...
 
  • #4
Other numerical integration methods are Rhomberg, adaptive quadrature and Gauss-Legendre.
 

1. What is a stochastic model?

A stochastic model is a mathematical representation of a system or process that involves random variables. It takes into account the uncertainty and variability inherent in real-world situations, making it useful for predicting outcomes and understanding complex systems.

2. How is the area under a curve calculated in a stochastic model?

In a stochastic model, the area under a curve is calculated by taking the integral of the curve, which represents the probability density function. This integral gives the cumulative distribution function, which can be used to calculate the probability of a certain event or outcome occurring.

3. What is the importance of finding the area under a curve in a stochastic model?

Finding the area under a curve in a stochastic model allows us to calculate probabilities and understand the likelihood of certain outcomes. This is crucial in fields such as finance, insurance, and risk management, where accurate predictions are necessary for decision making.

4. How does the use of a stochastic model differ from a deterministic model?

A stochastic model takes into account randomness and uncertainty, while a deterministic model assumes that all variables are known and fixed. This makes stochastic models more realistic and applicable to real-world situations, but also more complex to analyze and interpret.

5. What are some common applications of finding area under curve with stochastic models?

Some common applications of finding area under curve with stochastic models include risk assessment and management, financial forecasting, inventory management, and predicting outcomes in biological and environmental systems. Stochastic models are also used in fields such as engineering, economics, and epidemiology.

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