Data Preprocessing Questions
Data imputation using Markov chain Monte Carlo (MCMC) is a statistical technique used in data preprocessing to fill in missing values in a dataset. It involves using a Markov chain to simulate multiple possible values for the missing data based on the observed data and their relationships. MCMC imputation takes into account the uncertainty associated with the missing values and provides a range of plausible imputed values. This method is particularly useful when the missing data are not missing completely at random and have some dependence on other variables in the dataset.