Influence diagnostics for the power-normal Tobit model

Diagnostic analysis tools are studied for the censored power-normal Tobit regression model. We follow the Cook's (J. R. Stat. Soc., Ser. B, Stat. Methodol. 48 (1986) 133-169) approach, and several perturbation schemes are considered to detect influential observations. In particular, closed-form expressions of the normal curvatures for studying local influence are obtained under some perturbation schemes. The approach pursued also considers separate analysis for regression and scale-asymmetry parameters. Further, we define residuals to identify departures from the model assumptions, as well as to assess the overall goodness-of-fit of the censored power-normal Tobit regression model. The diagnostic measures developed are applied in a real data set for illustrative purposes.