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Markov Chain Monte Carlo: Metropolis-Hastings Algorithm for Distribution Simulation Coursework

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In this section, you are required to apply the Markov Chain Monte Carlo (MCMC) algorithm, specifically the Metropolis-Hastings algorithm. The goal is to generate random numbers for the probability distribution with the given probability density function: f(x)=12exp⁡(−∣x∣),f(x) = frac{1}{2} exp(-|x|),f(x)=21​exp(−∣x∣), where xxx takes values on the real line, and ∣x∣|x|∣x∣ represents the absolute value of …

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