"Markovian" meaning in English

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      "expansion": "Markov + -ian",
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  "etymology_text": "Markov + -ian, named for the Russian mathematician Andrey Markov.",
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      "expansion": "Markovian (not comparable)",
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  "lang": "English",
  "lang_code": "en",
  "pos": "adj",
  "senses": [
    {
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          "langcode": "en",
          "name": "Statistics",
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      "derived": [
        {
          "word": "Markovianity"
        },
        {
          "word": "non-Markovian"
        }
      ],
      "examples": [
        {
          "ref": "1992, Casella and George, Explaining the Gibbs Sampler, in: The American Statistician 46(3) 167–174",
          "text": "It is not immediately obvious that a random variable with distribution f(x) can be produced by the Gibbs sequence of (2.3) or that the sequence even converges. That this is so relies on the Markovian nature of the iterations, which we now develop in detail for the simple case of a 2 × 2 table with multinomial sampling."
        },
        {
          "ref": "2018, Guidolin and Pedio, Essentials of Time Series for Financial Applications, Academic Press",
          "text": "AR(p) models are simple univariate devices to capture the often-observed Markovian nature of financial and macroeconomic data […]",
          "type": "quotation"
        }
      ],
      "glosses": [
        "Exhibiting the Markov property, in which the conditional probability distribution of future states of the process, given the present state and all past states, depends only upon the present state and not on any past states."
      ],
      "id": "en-Markovian-en-adj-QjhO3I2A",
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      "raw_glosses": [
        "(statistics, of a process) Exhibiting the Markov property, in which the conditional probability distribution of future states of the process, given the present state and all past states, depends only upon the present state and not on any past states."
      ],
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        "of a process"
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      "tags": [
        "not-comparable"
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        "mathematics",
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      "translations": [
        {
          "code": "he",
          "lang": "Hebrew",
          "roman": "markóvi",
          "sense": "Exhibiting the Markov property",
          "word": "מרקובי"
        }
      ]
    }
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      "ipa": "/mɑɹˈkoʊvi.ən/",
      "tags": [
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  "word": "Markovian"
}

{
  "derived": [
    {
      "word": "Markovianity"
    },
    {
      "word": "non-Markovian"
    }
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        "2": "Markov",
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  "etymology_text": "Markov + -ian, named for the Russian mathematician Andrey Markov.",
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  "lang_code": "en",
  "pos": "adj",
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      "examples": [
        {
          "ref": "1992, Casella and George, Explaining the Gibbs Sampler, in: The American Statistician 46(3) 167–174",
          "text": "It is not immediately obvious that a random variable with distribution f(x) can be produced by the Gibbs sequence of (2.3) or that the sequence even converges. That this is so relies on the Markovian nature of the iterations, which we now develop in detail for the simple case of a 2 × 2 table with multinomial sampling."
        },
        {
          "ref": "2018, Guidolin and Pedio, Essentials of Time Series for Financial Applications, Academic Press",
          "text": "AR(p) models are simple univariate devices to capture the often-observed Markovian nature of financial and macroeconomic data […]",
          "type": "quotation"
        }
      ],
      "glosses": [
        "Exhibiting the Markov property, in which the conditional probability distribution of future states of the process, given the present state and all past states, depends only upon the present state and not on any past states."
      ],
      "links": [
        [
          "statistics",
          "statistics"
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      ],
      "raw_glosses": [
        "(statistics, of a process) Exhibiting the Markov property, in which the conditional probability distribution of future states of the process, given the present state and all past states, depends only upon the present state and not on any past states."
      ],
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        "of a process"
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      "ipa": "/mɑɹˈkoʊvi.ən/",
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  "translations": [
    {
      "code": "he",
      "lang": "Hebrew",
      "roman": "markóvi",
      "sense": "Exhibiting the Markov property",
      "word": "מרקובי"
    }
  ],
  "word": "Markovian"
}