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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Usawa wa Takwimu wa Usawazishaji wa Logisti×Regression ya Kiasi (Quantile Regression)×
NyanjaTakwimuEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili20011978
MwanzilishiCantoni & Ronchetti (2001); Bondell (2008)Koenker & Bassett
AinaRobust generalized linear model (binary outcome)Conditional quantile regression
Chanzo asiliaCantoni, E. & Ronchetti, E. (2001). Robust Inference for Generalized Linear Models. Journal of the American Statistical Association, 96(455), 1022-1030. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Majina mbadalarobust binary regression, weighted logistic regression, Mallows-type logistic regression, Robust Lojistik Regresyonconditional quantile regression, regression quantiles, Kantil Regresyon
Zinazohusiana55
MuhtasariRobust Logistic Regression is a variant of logistic regression that is resistant to outliers and leverage points, fitting a binary or categorical outcome with Mallows-type weighted estimation. The robust framework for generalized linear models was developed by Cantoni and Ronchetti (2001), with a weighting approach later refined by Bondell (2008).Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
ScholarGateSeti ya data
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Robust Logistic Regression · Quantile Regression. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare