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R Function for Simulating Gaussian Processes

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This semester my studies all involve one key mathematical object: Gaussian processes. I’m taking a course on stochastic processes (which will talk about Wiener processes, a type of Gaussian process and arguably the most common) and mathematical finance, which involves stochastic differential equations (SDEs) used for derivative pricing, including in the Black-Scholes-Merton equation. Then I’m involved in a Gaussian process and stochastic calculus reading group. So these processes will take up a lot of my attention. In a conversation about these processes with a fellow graduate student I was explaining the idea that different kernels (covariance functions, or ) define different Gaussian processes and simply changing the kernel will produce new processes with completely different properties. Let be the kernel of a process. is the kernel associated with the Wiener process and produces a process that is continuous everywhere but…
Original Post: R Function for Simulating Gaussian Processes