JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2005, Vol. 29 ›› Issue (04): 69-72.doi: 10.3969/j.jssn.1000-2006.2005.04.017

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Influence Graph for the Nonlinear Regression with Heteroscedasticity

XIE Feng-chang1, LI Yong2   

  1. 1. Department of Mathematics Nanjing Agricultural University, Nanjing 210095, China; 2. Department of Mathematics Southeast University, Nanjing 210096, China
  • Online:2005-08-18 Published:2005-08-18

Abstract: In ordinary regression analysis, the homoscedasticity of random error is a basic assumption. But the rationality of these assumptions for variance is doubtable. This paper takes the weighted nonlinear regression model as a perturbed version of a homoscedastic regression model and develops the tests for heteroscedasticity based on normal curvature of its influence graph. Based on this fact,the modified score statistic was discussed in detail. Final-[y these new statistics was applied to two concrete numerical examples.

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