{
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  "Package": "snha",
  "Type": "Package",
  "Title": "Creating Correlation Networks using St. Nicolas House Analysis",
  "Version": "0.4.0",
  "Date": "2026-04-16",
  "Author": "Detlef Groth",
  "Authors@R": "c(person(\"Detlef\",\"Groth\", role=c(\"aut\", \"cre\"),\nemail = \"dgroth@uni-potsdam.de\",\ncomment=c(ORCID=\"0000-0002-9441-3978\")))",
  "Maintainer": "Detlef Groth <dgroth@uni-potsdam.de>",
  "Description": "Create correlation networks using St. Nicolas House\nAnalysis ('SNHA'). The package can be used for visualizing\nmultivariate data similar to Principal Component Analysis or\nMultidimensional Scaling using a ranking approach. In contrast\nto 'MDS' and 'PCA', 'SNHA' uses a network approach to explore\ninteracting variables. For details see 'Hermanussen et. al.\n2021', <doi:10.3390/ijerph18041741>.",
  "URL": "https://github.com/mittelmark/snha",
  "BugReports": "https://github.com/mittelmark/snha/issues",
  "VignetteBuilder": "knitr",
  "License": "MIT + file LICENSE",
  "LazyData": "yes",
  "Language": "en-US",
  "Encoding": "UTF-8",
  "NeedsCompilation": "no",
  "Collate": "ll.R asgp.R priv.R snha.R mgraph.R",
  "Repository": "https://mittelmark.r-universe.dev",
  "Date/Publication": "2026-04-16 06:46:09 UTC",
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    "email": "dgroth@uni-potsdam.de",
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      "name": "v0.2.1",
      "date": "2025-12-11"
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  "_topics": [
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    "network",
    "network-analysis",
    "network-reconstruction"
  ],
  "_stars": 6,
  "_contributors": [
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      "user": "mittelmark",
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    "type": "user",
    "name": "Detlef Groth",
    "description": "Postdoc at University of Potsdam.\r\nGiving, Lectures in Bioinformatics, Machine Learning, Statistics, Programming and Molecular Biology."
  },
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  "_searchresults": 7,
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  "_assets": [
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    "extra/NEWS.txt",
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  "_realowner": "mittelmark",
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  "_releases": [
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      "date": "2023-03-14"
    }
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    "as.list.snha",
    "mgraph",
    "mgraph_accuracy",
    "mgraph_autonames",
    "mgraph_d2u",
    "mgraph_degree",
    "mgraph_harmonic_centrality",
    "mgraph_lmc",
    "mgraph_lms",
    "mgraph_nd",
    "mgraph_node_colors",
    "mgraph_nodeColors",
    "mgraph_shortest_paths",
    "mgraph_trf",
    "mgraph_u2d",
    "plot.mgraph",
    "plot.snha",
    "snha",
    "snha_corrplot",
    "snha_get_chains",
    "snha_graph2data",
    "snha_layout",
    "snha_ll",
    "snha_mi",
    "snha_rsquare"
  ],
  "_datasets": [
    {
      "name": "decathlon88",
      "title": "Men Decathlon data from the 1988 Olympics",
      "object": "decathlon88",
      "class": [
        "data.frame"
      ],
      "fields": [
        "disc",
        "high",
        "jave",
        "long",
        "pole",
        "shot",
        "X100",
        "X110",
        "X1500",
        "X400"
      ],
      "rows": 33,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "snha-package",
      "title": "snha package - association chain graphs from correlation networks",
      "topics": [
        "snha-package"
      ]
    },
    {
      "page": "as.list.snha",
      "title": "return a list representation for an snha graph object",
      "topics": [
        "as.list.snha"
      ]
    },
    {
      "page": "decathlon88",
      "title": "Men Decathlon data from the 1988 Olympics",
      "topics": [
        "decathlon88"
      ]
    },
    {
      "page": "mgraph",
      "title": "create a mgraph object, an adjacency matrix of a specific type",
      "topics": [
        "mgraph"
      ]
    },
    {
      "page": "mgraph_accuracy",
      "title": "quality measures for a predicted graph",
      "topics": [
        "mgraph_accuracy"
      ]
    },
    {
      "page": "mgraph_autonames",
      "title": "create names for nodes and other data structures",
      "topics": [
        "mgraph_autonames"
      ]
    },
    {
      "page": "mgraph_d2u",
      "title": "create an undirected graph out of a directed graph",
      "topics": [
        "mgraph_d2u"
      ]
    },
    {
      "page": "mgraph_degree",
      "title": "return the number of edges for each node",
      "topics": [
        "mgraph_degree"
      ]
    },
    {
      "page": "mgraph_harmonic_centrality",
      "title": "return the harmonic centraility for each node of a graph",
      "topics": [
        "mgraph_harmonic_centrality"
      ]
    },
    {
      "page": "mgraph_lmc",
      "title": "using linear models to check the create snha graph",
      "topics": [
        "mgraph_lmc"
      ]
    },
    {
      "page": "mgraph_lms",
      "title": "linear model backward variable selection",
      "topics": [
        "mgraph_lms"
      ]
    },
    {
      "page": "mgraph_nd",
      "title": "network deconvolved data matrix using the algorithm of Feizi et. al. 2013",
      "topics": [
        "mgraph_nd"
      ]
    },
    {
      "page": "mgraph_nodeColors",
      "title": "create node colors for directed graphs",
      "topics": [
        "mgraph_nodeColors",
        "mgraph_node_colors"
      ]
    },
    {
      "page": "mgraph_shortest_paths",
      "title": "caluclate shortest paths for a graph using BFS search",
      "topics": [
        "mgraph_shortest_paths"
      ]
    },
    {
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      "title": "checking possible chains with 3 nodes for triad structures",
      "topics": [
        "mgraph_trf"
      ]
    },
    {
      "page": "mgraph_u2d",
      "title": "reate a directed graph out of an undirected graph",
      "topics": [
        "mgraph_u2d"
      ]
    },
    {
      "page": "plot.snha",
      "title": "display network or correlation matrices of snha graphs",
      "topics": [
        "plot.mgraph",
        "plot.snha"
      ]
    },
    {
      "page": "snha",
      "title": "Initialize a snha object with data.",
      "topics": [
        "snha"
      ]
    },
    {
      "page": "snha_corrplot",
      "title": "visualize a matrix of pairwise correlations",
      "topics": [
        "snha_corrplot"
      ]
    },
    {
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      "title": "Return the chains of a snha graph as data frame",
      "topics": [
        "snha_get_chains"
      ]
    },
    {
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      "title": "create correlated data for the given adjacency matrix representing a directed graph or an undirected graph",
      "topics": [
        "snha_graph2data"
      ]
    },
    {
      "page": "snha_layout",
      "title": "Determine graph layouts",
      "topics": [
        "snha_layout"
      ]
    },
    {
      "page": "snha_ll",
      "title": "log-likelihood for the given snha graph and the given chain",
      "topics": [
        "snha_ll"
      ]
    },
    {
      "page": "snha_mi",
      "title": "mutual information for two vectors or a matrix",
      "topics": [
        "snha_mi"
      ]
    },
    {
      "page": "snha_rsquare",
      "title": "linear model based r-square values for given data and graph",
      "topics": [
        "snha_rsquare"
      ]
    }
  ],
  "_readme": "https://github.com/mittelmark/snha/raw/HEAD/README.md",
  "_rundeps": [
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      "title": "Tutorial on the snha package",
      "author": "Detlef Groth, University of Potsdam, Germany",
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