Сравнение методов

	Кросс-валидация	Метод Монте-Карло	Тест перестановок (рандомизация)
Область	Принятие решений	Принятие решений	Статистика
Семейство	MCDM	MCDM	Regression model
Год появления	1974	1949	2005
Автор метода	Stone, M.	Metropolis, N., Ulam, S.	Good (2005); Edgington & Onghena (2007); resampling tradition
Тип	Robustness wrapper — k-fold cross-validation for MCDM stability	Robustness wrapper — Monte Carlo uncertainty propagation	Nonparametric resampling test
Основополагающий источник	Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society Series B	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association	Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
Другие названия	—	—	randomization test, exact permutation test, re-randomization test, Permütasyon Testi
Связанные	0	0	5
Сводка	CROSS-VALIDATION (Cross-Validation — k-fold hold-out validation of MCDM decision consistency) is a ranking multi-criteria decision-making (MCDM) method introduced by Stone, M. in 1974. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value.