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Inferencia de Aleatorización Exacta de Fisher×Regresión Cuantílica (Variantes No Paramétricas)×
CampoEstadísticaEstadística
FamiliaRegression modelRegression model
Año de origen19351978
Autor originalRonald A. FisherKoenker & Bassett
TipoExact permutation-based inferenceQuantile regression (nonparametric variants)
Fuente seminalFisher, R. A. (1935). The Design of Experiments. Oliver & Boyd. link ↗Koenker, R. & Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Aliasfisher randomization test, permutation inference, exact randomization test, randomizasyon çıkarımı (fisher exact randomization)quantile regression, median regression, distribution-free quantile regression, Kantil Regresyon (Nonparametric Varyantlar)
Relacionados55
ResumenRandomization inference, introduced by Ronald A. Fisher in The Design of Experiments (1935), computes an exact p-value by evaluating a test statistic across all possible treatment assignments under Fisher's sharp null hypothesis. It is regarded as the gold standard for analysing designed experiments because its validity rests on the known assignment mechanism rather than on distributional assumptions.Quantile regression, introduced by Koenker and Bassett in 1978, models a chosen conditional quantile (such as the median or the 25th and 75th percentiles) of a continuous outcome rather than its mean. Its nonparametric variants fit these quantile relationships without assuming a distribution for the errors, making them a robust complement to mean-based regression on skewed data.
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ScholarGateComparar métodos: Randomization Inference · Nonparametric Quantile Regression. Recuperado el 2026-06-15 de https://scholargate.app/es/compare