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  2. Chauvenet's criterion - Wikipedia

    en.wikipedia.org/wiki/Chauvenet's_criterion

    The idea behind Chauvenet's criterion finds a probability band that reasonably contains all n samples of a data set, centred on the mean of a normal distribution.By doing this, any data point from the n samples that lies outside this probability band can be considered an outlier, removed from the data set, and a new mean and standard deviation based on the remaining values and new sample size ...

  3. Weighted sum model - Wikipedia

    en.wikipedia.org/wiki/Weighted_Sum_Model

    In decision theory, the weighted sum model (WSM), [1] [2] also called weighted linear combination (WLC) [3] or simple additive weighting (SAW), [4] is the best known and simplest multi-criteria decision analysis (MCDA) / multi-criteria decision making method for evaluating a number of alternatives in terms of a number of decision criteria.

  4. Best worst method - Wikipedia

    en.wikipedia.org/wiki/Best_worst_method

    Best Worst Method (BWM) is a multi-criteria decision-making (MCDM) method that was proposed by Dr. Jafar Rezaei in 2015. [1] [2] The method is used to evaluate a set of alternatives with respect to a set of decision criteria. The BWM is based on pairwise comparisons of the decision criteria. That is, after identifying the decision criteria by ...

  5. Weighted product model - Wikipedia

    en.wikipedia.org/wiki/Weighted_product_model

    The weighted product model (WPM) is a popular multi-criteria decision analysis (MCDA) / multi-criteria decision making (MCDM) method. It is similar to the weighted sum model (WSM) in that it produces a simple score, but has the very important advantage of overcoming the issue of 'adding apples and pears' i.e. adding together quantities measured in different units.

  6. Bayesian information criterion - Wikipedia

    en.wikipedia.org/wiki/Bayesian_information_criterion

    It is based, in part, on the likelihood function and it is closely related to the Akaike information criterion (AIC). When fitting models, it is possible to increase the maximum likelihood by adding parameters, but doing so may result in overfitting. Both BIC and AIC attempt to resolve this problem by introducing a penalty term for the number ...

  7. TOPSIS - Wikipedia

    en.wikipedia.org/wiki/TOPSIS

    The weights of the criteria in TOPSIS method can be calculated using Ordinal Priority Approach, Analytic hierarchy process, etc. An assumption of TOPSIS is that the criteria are monotonically increasing or decreasing. Normalisation is usually required as the parameters or criteria are often of incongruous dimensions in multi-criteria problems.

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  9. Peirce's criterion - Wikipedia

    en.wikipedia.org/wiki/Peirce's_criterion

    The test, based on a likelihood ratio type of argument, had the distinction of producing an international debate on the wisdom of such actions (Anscombe, 1960, Rider, 1933, Stigler, 1973a)." Peirce's criterion is derived from a statistical analysis of the Gaussian distribution. Unlike some other criteria for removing outliers, Peirce's method ...

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