Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Regressão por Mínimos Quadrados Truncados (LTS)× | Regressão Quantílica× | |
|---|---|---|
| Área≠ | Estatística | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1984 | 1978 |
| Autor original≠ | Peter J. Rousseeuw | Koenker & Bassett |
| Tipo≠ | Robust linear regression | Conditional quantile regression |
| Fonte seminal≠ | Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Outros nomes≠ | LTS, least trimmed squares regression, trimmed least squares, robust regression | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Relacionados | 5 | 5 |
| Resumo≠ | Least Trimmed Squares is a robust linear regression method introduced by Peter J. Rousseeuw in 1984. Instead of fitting all residuals, it estimates the coefficients by minimising the sum of only the h smallest squared residuals, which gives it a breakdown point of up to 50% and reliable estimates on data heavily contaminated by outliers. | 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. |
| ScholarGateConjunto de dados ↗ |
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