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How can you control the number of principal components used during scoring?

You can specify the number of principal components to use by setting the "npc" parameter within the "output" list. The default value is 4.

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On: fPcaScore

collection={{collection-1} <, {collection-2}, ...>}

defines a set of variables that are treated as a single effect that has multiple degrees of freedom. The collection value can be one or more of the following:details=TRUE | FALSEwhen set to True, requests a table that shows additional details that are related to this effect.DefaultFALSE* name="string"specifies the name of the effect.* vars={"variable-name-1" }&nbsp;specifies a set of variables that are treated as a single effect that has multiple degrees of freedom. The columns in the design matrix that are contributed by a collection effect are the design columns of its constituent variables in the order in which they appear in the definition of the collection effect.

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On: gvarcluster

Can I run tests for special causes if my control limits are not 3-sigma?

Yes, by setting the `no3SigmaCheck` parameter to True, you can enable tests for special causes even when the control limits are not the standard three-sigma limits.

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On: cChart

absFreq

Use absolute of frequencies, useful when frequency data are correlations. Alias: absFrequency. Default: FALSE.

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On: hypergroup

What is a connected component in a graph?

A connected component of a graph is a subgraph in which any two vertices are connected to each other by paths, and which is connected to no additional vertices in the supergraph. For a directed graph, there are weakly and strongly connected components.

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On: connectedComponents