Finite mixture models

Finite mixture models are statistical tools used to analyze data that comes from a combination of different groups or sources. Imagine trying to understand a mixed bag of candies—each type has its own flavor and characteristics. Similarly, these models assume the data is generated from several distinct groups, called components, each with its own pattern. By identifying these groups, the model helps us understand the underlying structure and estimate the properties of each subgroup. This approach is useful in fields like marketing, biology, and social sciences, where data often reflects a mix of different populations.