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Analysis options for sdo.analyze


Specify analysis method and method options for sensitivity analysis using sdo.analyze.




opt = sdo.AnalyzeOptions creates an sdo.AnalyzeOptions object and assigns default values to the properties.

opt = sdo.AnalyzeOptions(Method=method_name) sets the Method property as the value method_name.

Before R2021a, use the equivalent syntax opt = sdo.AnalyzeOptions("Method",method_name).

To change a property value after you create the object, use dot notation. For example:

opt = sdo.AnalyzeOptions;
opt.Method = "StandardizedRegression";
opt.MethodOptions = "Ranked";


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Analysis method used by sdo.analyze, specified as one of the following, or a string array or cell array of character vectors containing a subset of the following:

  • "Correlation" — Calculates the correlation coefficients, R. Use to analyze how a model parameter and the cost function outputs are correlated.

    R is calculated as follows:


    x and y are the input arguments of sdo.analyze.

    R values are in the [-1, 1] range. The (i,j) entry of R indicates the correlation between x(i) and y(j).

    • R(i,j) > 0 — Variables have positive correlation. The variables increase together.

    • R(i,j) = 0 — Variables have no correlation.

    • R(i,j) < 0 — Variables have negative correlation. As one variable increases, the other decreases.

  • "PartialCorrelation" (Requires a Statistics and Machine Learning Toolbox™ license) — Calculates the partial correlation coefficients, R. Use to analyze how a model parameter and the cost function are correlated, adjusting to remove the effect of the other parameters.

    R is calculated using partialcorri (Statistics and Machine Learning Toolbox) in the Statistics and Machine Learning Toolbox software.

  • "StandardizedRegression" — Calculates the standardized regression coefficients, R. Use when you expect that the model parameters linearly influence the cost function.

    R is calculated as follows:


    Consider a single sample (x1,...,xNp) and the corresponding single output, y. bx is the regression coefficient vector calculated using least squares assuming a linear model y^=b0+i=1Npb^xixi. R standardizes each element of bx by multiplying it with the ratio of the standard deviation of the corresponding x sample (σx) to the standard deviation of y (σy).

  • "All" — The software calculates results for all applicable combinations of Method and MethodOptions. This option may be time consuming if you have a large sample set with many parameters and many different cost/constraint outputs.

For x (Ns-by-Np) and y (Ns-by-Nc), all the methods calculate R as an Np-by-Nc table. Here Ns is the number of samples, Np is the number of model parameters, and Nc is the number of cost/constraint function evaluations.

Example: Method="StandardizedRegression" or Method='StandardizedRegression' calculates the standardized regression coefficients

Example: Method=["Correlation","StandardizedRegression"] or Method={'Correlation','StandardizedRegression'} calculates both the correlation coefficients and the standardized regression coefficients

Data Types: char | string

Analysis method option that sdo.analyze uses, specified as one of the following values:

  • "Linear" — Pearson analysis.

    Applicable for all methods.

  • "Ranked" — Ranked transformation or Spearman analysis.

    Applicable for all methods.

  • "Kendall" — Kendall’s tau.

    Applicable when Method is specified as "Correlation".

  • "AllApplicable" — Calculates each applicable combination of Method and MethodOptions.

    Applicable when Method is specified as "All".

For more information about these options, see Analyze Relation Between Parameters and Design Requirements.

Example: MethodOptions="Ranked" or Method='Ranked' specifies the ranked transformation option.

Data Types: char | string


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Create an sdo.AnalyzeOptions object.

opt = sdo.AnalyzeOptions;

Set object properties using dot notation.

opt.Method = "PartialCorrelation";
opt.MethodOptions = "Ranked";

Version History

Introduced in R2014a