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Added functionSignatures.json in toolbox\multivariate:
- Added code suggestions to CorAna, it has 2 mutually exclusive syntaxes that hide unnecessary inputs when N is a table. - Added code suggestions to corrNominal, it has 2 mutually exclusive syntaxes that hide unnecessary inputs when N is a table. - Added code suggestions to corrOrdinal, it has 2 mutually exclusive syntaxes that hide unnecessary inputs when N is a table. Typedefs changes and additions inside multivariate\functionSignatures.json: - Added complementary inputs to the Typedefs at the start of document for the function CorAna, corrNominal and corrOrdinal Fixed Typos in documentation: - In CorAna.m, at line 105, changed Sup.r in Sup.c
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‎toolbox/multivariate/CorAna.m‎

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% of the supplementary units can be given using
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% Sup.Lc as a cell array of strings.
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% Sup.Lc = cell array of strings containing the labels of the
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% supplementary units, if Sup.r is a 2D numeric array.
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% supplementary units, if Sup.c is a 2D numeric array.
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% Example - 'Sup', Sup=struct; Sup.c={'c2' 'c4'}
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% Data Types - struct
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% REMARK: The default value of Sup is a missing

‎toolbox/multivariate/functionSignatures.json‎

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{
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"_schemaVersion": "1.0.0",
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"_typedefs": {
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"Lr": {
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"purpose":"Cell array of strings containing the labels of the rows of the input",
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"type":["cell", "size=1,N"],
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"elements":{
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"type":[["string"], ["char"]]
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}
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},
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"Lc": {
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"purpose":"Cell array of strings containing the labels of the columns of the input",
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"type":["cell", "size=1,N"],
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"elements":{
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"type":[["string"], ["char"]]
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}
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},
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"Sup_CorAna": {
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"purpose":"Structure containing indexes or names of supplementary rows or columns",
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"type":"struct",
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"fields":[
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{"name":"r", "type":[["single", "vector"], ["double", "vector"], ["cell"]], "purpose":"vector containing row indexes or vector of cell array of strings or table or 2D numeric array, containing supplementary rows"},
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{"name":"Lr", "type":"cell", "purpose":"cell array of strings containing the labels of the supplementary units if Sup.r is a 2D numeric array"},
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{"name":"c", "type":[["single", "vector"], ["double", "vector"], ["cell"]], "purpose":"vector containing column indexes or vector of cell array of strings or table or 2D numeric array use as supplementary columns, or table or 2D numeric array containing supplementary rows"},
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{"name":"Lc", "type":"cell", "purpose":"cell array of strings containing the labels of the supplementary units if Sup.c is a 2D numeric array"}
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]
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},
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"Plots_CorAna": {
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"purpose":"Correspondence analysis plots additional options",
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"type":"struct",
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"fields":[
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{"name":"alpha", "type":[["numeric", "scalar"], ["char"], ["string"]], "purpose":"Type of plot displayed"},
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{"name":"FontSize", "type":["numeric", "scalar"], "purpose":"Font size of labels"},
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{"name":"MarkerSize", "type":["numeric", "scalar"], "purpose":"Size of plot markers"}
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]
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}
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},
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"CorAna":
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{
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"inputs":
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[
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{"name":"N", "kind":"required", "type":[["single", "2d"], ["double", "2d"]], "purpose":"Contingency table (default) or n-by-2 input dataset"},
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{"name":"k", "kind":"namevalue", "type":["double", "size=1,1"], "purpose":"Number of dimensions to retain"},
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{"name":"Lr", "kind":"namevalue", "type":"cell:Lr", "purpose":"Vector of row labels"},
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{"name":"Lc", "kind":"namevalue", "type":"cell:Lc", "purpose":"Vector of column labels"},
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{"name":"Sup", "kind":"namevalue", "type":"struct:Sup_CorAna", "purpose":"Structure containing indexes or names of supplementary rows or columns"},
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{"name":"datamatrix", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Data matrix or contingency table"},
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{"name":"plots", "kind":"namevalue", "type":[["struct:Plots_CorAna"], ["numeric", "scalar", "choices={0,1}"]], "purpose":"Display plots on screen"},
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{"name":"dispresults", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display results on screen"},
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{"name":"d1", "kind":"namevalue", "type":["numeric", "scalar"], "purpose":"Dimension to show on the horizontal axis"},
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{"name":"d2", "kind":"namevalue", "type":["numeric", "scalar"], "purpose":"Dimension to show on the vertical axis"}
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],
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"outputs":
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[
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{"name":"out", "type":"struct", "purpose":"Structure containing the output of the function"}
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],
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"description":"Perform correspondence analysis"
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},
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"CorAna":
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{
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"inputs":
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[
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{"name":"N", "kind":"required", "type":"table", "purpose":"Contingency table (default) or n-by-2 input dataset"},
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{"name":"k", "kind":"namevalue", "type":["double", "size=1,1"], "purpose":"Number of dimensions to retain"},
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{"name":"Sup", "kind":"namevalue", "type":"struct:Sup_CorAna", "purpose":"Structure containing indexes or names of supplementary rows or columns"},
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{"name":"datamatrix", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Data matrix or contingency table"},
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{"name":"plots", "kind":"namevalue", "type":[["struct:Plots_CorAna"], ["numeric", "scalar", "choices={0,1}"]], "purpose":"Display plots on screen"},
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{"name":"dispresults", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display results on screen"},
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{"name":"d1", "kind":"namevalue", "type":["numeric", "scalar"], "purpose":"Dimension to show on the horizontal axis"},
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{"name":"d2", "kind":"namevalue", "type":["numeric", "scalar"], "purpose":"Dimension to show on the vertical axis"}
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],
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"outputs":
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[
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{"name":"out", "type":"struct", "purpose":"Structure containing the output of the function"}
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],
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"description":"Perform correspondence analysis"
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},
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"corrNominal":
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{
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"inputs":
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[
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{"name":"N", "kind":"required", "type":[["single", "2d"], ["double", "2d"]], "purpose":"Contingency table (default) or n-by-2 input dataset"},
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{"name":"Conflev", "kind":"namevalue", "type":["double", "scalar"], "purpose":"Confidence level to be used to compute confidence intervals"},
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{"name":"conflimMethodCramerV", "kind":"namevalue", "type":["char", "choices={'ncchisq', 'ncchisqadj', 'fisher', 'fisheradj'}"], "purpose":"Method to compute confidence inteval for Cramer's V"},
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{"name":"dispresults", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display results on screen"},
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{"name":"Lr", "kind":"namevalue", "type":"cell:Lr", "purpose":"Vector of row labels"},
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{"name":"Lc", "kind":"namevalue", "type":"cell:Lc", "purpose":"Vector of column labels"},
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{"name":"datamatrix", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Data matrix or contingency table"},
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{"name":"NoStandardErrors", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Just indexes without standard errors and p-values"},
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{"name":"plots", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display balloonplot and pareto plot of squared Pearson residuals"}
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],
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"outputs":
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[
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{"name":"out", "type":"struct", "purpose":"Structure containing the output of the function"}
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],
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"description":"corrNominal measures strength of association between two unordered (nominal) categorical variables"
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},
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"corrNominal":
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{
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"inputs":
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[
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{"name":"N", "kind":"required", "type":"table", "purpose":"Contingency table (default) or n-by-2 input dataset"},
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{"name":"Conflev", "kind":"namevalue", "type":["double", "scalar"], "purpose":"Confidence level to be used to compute confidence intervals"},
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{"name":"conflimMethodCramerV", "kind":"namevalue", "type":["char", "choices={'ncchisq', 'ncchisqadj', 'fisher', 'fisheradj'}"], "purpose":"Method to compute confidence inteval for Cramer's V"},
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{"name":"dispresults", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display results on screen"},
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{"name":"datamatrix", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Data matrix or contingency table"},
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{"name":"NoStandardErrors", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Just indexes without standard errors and p-values"},
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{"name":"plots", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display balloonplot and pareto plot of squared Pearson residuals"}
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],
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"outputs":
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[
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{"name":"out", "type":"struct", "purpose":"Structure containing the output of the function"}
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],
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"description":"corrNominal measures strength of association between two unordered (nominal) categorical variables"
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},
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"corrOrdinal":
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{
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"inputs":
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[
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{"name":"N", "kind":"required", "type":[["single", "2d"], ["double", "2d"]], "purpose":"Contingency table (default) or n-by-2 input dataset"},
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{"name":"NoStandardErrors", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Just indexes without standard errors and p-values"},
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{"name":"dispresults", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display results on screen"},
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{"name":"Lr", "kind":"namevalue", "type":"cell:Lr", "purpose":"Vector of row labels"},
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{"name":"Lc", "kind":"namevalue", "type":"cell:Lc", "purpose":"Vector of column labels"},
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{"name":"datamatrix", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Data matrix or contingency table"},
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{"name":"Conflev", "kind":"namevalue", "type":["double", "scalar"], "purpose":"Confidence level to be used to compute confidence intervals"},
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{"name":"plots", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display balloonplot and pareto plot of individual contributions to C-D"}
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],
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"outputs":
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[
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{"name":"out", "type":"struct", "purpose":"Structure containing the output of the function"}
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],
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"description":"corrOrdinal measures strength of association between two ordered categorical variables"
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},
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"corrOrdinal":
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{
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"inputs":
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[
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{"name":"N", "kind":"required", "type":"table", "purpose":"Contingency table (default) or n-by-2 input dataset"},
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{"name":"NoStandardErrors", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Just indexes without standard errors and p-values"},
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{"name":"dispresults", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display results on screen"},
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{"name":"datamatrix", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Data matrix or contingency table"},
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{"name":"Conflev", "kind":"namevalue", "type":["double", "scalar"], "purpose":"Confidence level to be used to compute confidence intervals"},
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{"name":"plots", "kind":"namevalue", "type":["logical", "scalar"], "purpose":"Display balloonplot and pareto plot of individual contributions to C-D"}
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],
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"outputs":
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[
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{"name":"out", "type":"struct", "purpose":"Structure containing the output of the function"}
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],
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"description":"corrOrdinal measures strength of association between two ordered categorical variables"
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}
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}

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