In probability theory and statistics, a mixture is a combination of two or more probability distributions. The concept arises in two contexts: A mixture defining a new probability distribution from some existing ones, as in a mixture density. Here the main problem is to derive the theoretical properties of the new distribution. A mixture used as a statistical model such as is often used for statistical classification.
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- In probability theory and statistics, a mixture is a combination of two or more probability distributions. The concept arises in two contexts: A mixture defining a new probability distribution from some existing ones, as in a mixture density. Here the main problem is to derive the theoretical properties of the new distribution. A mixture used as a statistical model such as is often used for statistical classification. The model may represent the population from which observations arise as a mixture density, but the problem is that of a mixture model, in which a data classification hypothesis represents an overall distribution as a sum of separate distributions (representing separate populations) and the task is to infer from which population each observation arises.
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- In probability theory and statistics, a mixture is a combination of two or more probability distributions. The concept arises in two contexts: A mixture defining a new probability distribution from some existing ones, as in a mixture density. Here the main problem is to derive the theoretical properties of the new distribution. A mixture used as a statistical model such as is often used for statistical classification.
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