Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Sensitivity Analysis in Latent Root Regression

  • Published : 1994.12.01
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Abstract

We Propose a method of sensitivity analysis in latent root regression analysis (LRRA). For this purpose we derive the quantities ${\beta\limits^\wedge \;_{LRR}}^{(1)}$, which correspond to the theoretical influence function $I(x, y \;;\;\beta\limits^\wedge \;_{LRR})$ for the regression coefficient ${\beta\limits^\wedge}_{LRR}$ based on LRRA. We give a numerical example for illustration and also investigate numerically the relationship between the estimated values of ${\beta\limits^\wedge \;_{LRR}}^{(1)}$ with the values of the other measures called sample influence curve(SIC) based on the recomputation for the data with a single observation deleted. We also discuss the comparision among the results of LRRA, ordinary least square regression analysis (OLSRA) and ridge regression analysis(RRA).

Keywords

References

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