Probabilistic SA method

The method estimates the following sensitivity indices:

Sensitivity index	When to Use
Pearson product-moment correlation coefficient (Pearson)	Computes the correlation coefficient. Interesting when model is linearly depending on parameters.
Spearman's rank correlation coefficient (Spearman)	Computes the ranked correlation coefficient. Interesting when model is linearly or monotonically depending on parameters.
Standardized Regression Coefficient (SRC)	Sets up a regression model from the raw data. Interesting when model is linearly depending on parameters.
Standardized Rank Regression Coefficient (SRRC)	Sets up a regression model from the ranked data. Interesting when model is linearly or monotonically depending on parameters.
Partial Correlation Coefficient (PCC)	Computes the correlation coefficient taking into account the rest of the varying parameters. Interesting when model is linearly depending on parameters.
Partial Rank Correlation Coefficient (PRCC)	Computes the ranked correlation coefficient taking into account the rest of the varying parameters. Interesting when model is linearly or monotonically depending on parameters.
EASI first order correlation coefficient (EASI)	Quantifies the first order effects, if model is additive this will take into account the full variance.

The possible settings are:

Setting	Explanation
Iterations	The number of iterations per parameter. It equals the number of total model evaluations.
Enable correlation	Enables correlation between input parameters. The correlation matrix is defined in the correlation matrix editor.
Latin hypercube sampling	Uses latin hypercube sampling. If unchecked, ordinary Monte Carlo method is used.
Seed	The seed used by methods random number generator. If it is Auto, a random seed will be used each time.

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