Heteroscedasticity, multicollinearity and spatial autocorrelation By fitting linear regressions to different conditional quantiles of the range of a response variable, quantile regression overcomes the problem of heterogeneity of variance [ 34 ] and is thus well suited in the presence of heteroscedastic error (the Breusch-Pagan test fitted to a linear regression model is highly significant).
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Assessing whether the best land is cultivated first: A quantile analysis.
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