{
  "__type": "IngestedDoc",
  "__tag": 4010,
  "_content": {
    "Notes": {
      "__type": "Section",
      "__tag": 4015,
      "children": [
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "The row and column vectors must be one-dimensional, not empty, and each sum up to the same value. They cannot contain negative or noninteger entries."
            }
          ]
        },
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "Random elements from the distribution are generated either with Boyett's "
            },
            {
              "__type": "FootnoteReference",
              "__tag": 4066,
              "label": "1"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " or Patefield's algorithm "
            },
            {
              "__type": "FootnoteReference",
              "__tag": 4066,
              "label": "2"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": ". Boyett's algorithm has O(N) time and space complexity, where N is the total sum of entries in the table. Patefield's algorithm has O(K x log(N)) time complexity, where K is the number of cells in the table and requires only a small constant work space. By default, the "
            },
            {
              "__type": "InlineRole",
              "__tag": 4003,
              "value": "rvs",
              "domain": null,
              "role": null,
              "inventory": null
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " method selects the fastest algorithm based on the input, but you can specify the algorithm with the keyword "
            },
            {
              "__type": "InlineRole",
              "__tag": 4003,
              "value": "method",
              "domain": null,
              "role": null,
              "inventory": null
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": ". Allowed values are \"boyett\" and \"patefield\"."
            }
          ]
        },
        {
          "__type": "Admonition",
          "__tag": 4056,
          "kind": "versionadded",
          "base_type": "neutral",
          "children": [
            {
              "__type": "AdmonitionTitle",
              "__tag": 4055,
              "children": [
                {
                  "__type": "Text",
                  "__tag": 4046,
                  "value": "versionadded 1.10.0"
                }
              ]
            }
          ]
        }
      ],
      "title": [],
      "level": 0,
      "target": null
    },
    "Warns": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Raises": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Yields": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Methods": {
      "__type": "Section",
      "__tag": 4015,
      "children": [
        {
          "__type": "Parameters",
          "__tag": 4026,
          "children": [
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "logpmf(x)",
              "annotation": "",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Log-probability of table "
                    },
                    {
                      "__type": "InlineRole",
                      "__tag": 4003,
                      "value": "x",
                      "domain": null,
                      "role": null,
                      "inventory": null
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " to occur in the distribution."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "pmf(x)",
              "annotation": "",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Probability of table "
                    },
                    {
                      "__type": "InlineRole",
                      "__tag": 4003,
                      "value": "x",
                      "domain": null,
                      "role": null,
                      "inventory": null
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " to occur in the distribution."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "mean(row, col)",
              "annotation": "",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Mean table."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "rvs(row, col, size=None, method=None, random_state=None)",
              "annotation": "",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Draw random tables with given row and column vector sums."
                    }
                  ]
                }
              ]
            }
          ]
        }
      ],
      "title": [],
      "level": 0,
      "target": null
    },
    "Returns": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Summary": {
      "__type": "Section",
      "__tag": 4015,
      "children": [
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "Contingency tables from independent samples with fixed marginal sums."
            }
          ]
        }
      ],
      "title": [],
      "level": 0,
      "target": null
    },
    "Receives": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Warnings": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Attributes": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Parameters": {
      "__type": "Section",
      "__tag": 4015,
      "children": [
        {
          "__type": "Parameters",
          "__tag": 4026,
          "children": [
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "row",
              "annotation": "array_like",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Sum of table entries in each row."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "col",
              "annotation": "array_like",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Sum of table entries in each column."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "seed",
              "annotation": "{None, int, np.random.RandomState, np.random.Generator}, optional",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Used for drawing random variates. If "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "seed"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " is "
                    },
                    {
                      "__type": "InlineRole",
                      "__tag": 4003,
                      "value": "None",
                      "domain": null,
                      "role": null,
                      "inventory": null
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": ", the "
                    },
                    {
                      "__type": "InlineRole",
                      "__tag": 4003,
                      "value": "~np.random.RandomState",
                      "domain": null,
                      "role": null,
                      "inventory": null
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " singleton is used. If "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "seed"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " is an int, a new "
                    },
                    {
                      "__type": "InlineCode",
                      "__tag": 4051,
                      "value": "RandomState"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " instance is used, seeded with seed. If "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "seed"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " is already a "
                    },
                    {
                      "__type": "InlineCode",
                      "__tag": 4051,
                      "value": "RandomState"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " or "
                    },
                    {
                      "__type": "InlineCode",
                      "__tag": 4051,
                      "value": "Generator"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " instance, then that object is used. Default is "
                    },
                    {
                      "__type": "InlineRole",
                      "__tag": 4003,
                      "value": "None",
                      "domain": null,
                      "role": null,
                      "inventory": null
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "."
                    }
                  ]
                }
              ]
            }
          ]
        }
      ],
      "title": [],
      "level": 0,
      "target": null
    },
    "Extended Summary": {
      "__type": "Section",
      "__tag": 4015,
      "children": [
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "This is the distribution of random tables with given row and column vector sums. This distribution represents the set of random tables under the null hypothesis that rows and columns are independent. It is used in hypothesis tests of independence."
            }
          ]
        },
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "Because of assumed independence, the expected frequency of each table element can be computed from the row and column sums, so that the distribution is completely determined by these two vectors."
            }
          ]
        }
      ],
      "title": [],
      "level": 0,
      "target": null
    },
    "Other Parameters": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    }
  },
  "_ordered_sections": [
    "Summary",
    "Extended Summary",
    "Parameters",
    "Attributes",
    "Methods",
    "Returns",
    "Yields",
    "Receives",
    "Other Parameters",
    "Raises",
    "Warns",
    "Warnings",
    "Notes"
  ],
  "item_file": "/scipy/stats/_multivariate.py",
  "item_line": 6100,
  "item_type": "class",
  "aliases": [
    "scipy.stats._multivariate.random_table_gen"
  ],
  "example_section_data": {
    "__type": "Section",
    "__tag": 4015,
    "children": [
      {
        "__type": "Code",
        "__tag": 4050,
        "value": "from scipy.stats import random_table\n",
        "execution_status": "success"
      },
      {
        "__type": "Text",
        "__tag": 4046,
        "value": "\n"
      },
      {
        "__type": "Code",
        "__tag": 4050,
        "value": "row = [1, 5]\ncol = [2, 3, 1]\n",
        "execution_status": "success"
      },
      {
        "__type": "Code",
        "__tag": 4050,
        "value": "random_table.mean(row, col)\n",
        "execution_status": "failure"
      },
      {
        "__type": "Text",
        "__tag": 4046,
        "value": "\nAlternatively, the object may be called (as a function) to fix the row\nand column vector sums, returning a \"frozen\" distribution.\n\n"
      },
      {
        "__type": "Code",
        "__tag": 4050,
        "value": "dist = random_table(row, col)\ndist.rvs(random_state=123)\n",
        "execution_status": "success"
      }
    ],
    "title": [],
    "level": 0,
    "target": null
  },
  "see_also": [],
  "signature": {
    "__type": "SignatureNode",
    "__tag": 4029,
    "kind": "function",
    "parameters": [
      {
        "__type": "SigParam",
        "__tag": 4030,
        "name": "seed",
        "annotation": {
          "__type": "Empty",
          "__tag": 4031
        },
        "kind": "POSITIONAL_OR_KEYWORD",
        "default": "None"
      }
    ],
    "return_annotation": {
      "__type": "Empty",
      "__tag": 4031
    },
    "target_name": "random_table_gen"
  },
  "references": [
    ".. [1] J. Boyett, AS 144 Appl. Statist. 28 (1979) 329-332",
    ".. [2] W.M. Patefield, AS 159 Appl. Statist. 30 (1981) 91-97"
  ],
  "qa": "scipy.stats._multivariate:random_table_gen",
  "arbitrary": [],
  "local_refs": [
    "col",
    "col)",
    "logpmf(x)",
    "mean(row",
    "method=None",
    "pmf(x)",
    "random_state=None)",
    "row",
    "rvs(row",
    "seed",
    "size=None"
  ]
}