Computational statistics

The discipline applying computationally intensive algorithms to statistical problems where analytical solutions are unavailable or inadequate. Key methods include bootstrap resampling, Markov chain Monte Carlo (MCMC), permutation tests, the EM algorithm, and cross-validation. It bridges classical statistics and modern machine learning.