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Байесовская описательная статистика×Робастные описательные статистики×
ОбластьСтатистикаСтатистика
СемействоHypothesis testHypothesis test
Год появления1763/18121960s–1970s
Автор методаThomas Bayes / Pierre-Simon LaplaceJohn W. Tukey, Peter J. Huber, Frank Hampel
ТипBayesian parameter estimationResistant summary measures
Основополагающий источникGelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165
Другие названияBayesian summaries, posterior descriptives, Bayesian parameter estimation, credible-interval summariesresistant statistics, outlier-resistant summary statistics, robust summary measures, robust location and scale estimation
Связанные55
СводкаBayesian descriptive statistics summarizes data by combining observed information with prior knowledge through Bayes' theorem, yielding posterior distributions over parameters such as the mean and variance. Instead of point estimates and p-values, results are expressed as posterior means, medians, and credible intervals that carry a direct probability interpretation.Robust descriptive statistics summarize the location, spread, and shape of a dataset using measures that remain meaningful even when a fraction of the data contains outliers or severe departures from normality. Core tools include the median, trimmed mean, interquartile range (IQR), and median absolute deviation (MAD), all of which are resistant to contamination that would distort the classic mean and standard deviation.
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  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Bayesian descriptive statistics · Robust Descriptive Statistics. Получено 2026-06-15 из https://scholargate.app/ru/compare