Salīdzināt metodes

	Krustiskā validācija	Monte Carlo simulācija	Permutācijas (randomizācijas) tests
Nozare	Lēmumu pieņemšana	Lēmumu pieņemšana	Statistika
Saime	MCDM	MCDM	Regression model
Izcelsmes gads	1974	1949	2005
Autors	Stone, M.	Metropolis, N., Ulam, S.	Good (2005); Edgington & Onghena (2007); resampling tradition
Tips	Robustness wrapper — k-fold cross-validation for MCDM stability	Robustness wrapper — Monte Carlo uncertainty propagation	Nonparametric resampling test
Pirmavots	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
Citi nosaukumi	—	—	randomization test, exact permutation test, re-randomization test, Permütasyon Testi
Saistītās	0	0	5
Kopsavilkums	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.