In this paper, we provide general bounds on the mean absolute difference and difference of moments of a random variable X and a perturbation rd (X), when | %DIFDELCMD < {\rm %%% rd (x)-x | \leq \epsilon |x| or |%DIFDELCMD < {\rm %%% rd (x)-x| \leq \delta which depend linearly on \epsilon and \delta.
<meaning-changed> In this paper, we provide general bounds on the mean absolute difference and difference of moments of a random variable X and a perturbation rd (X), when | %DIFDELCMD < {\rm %%% rd (x)-x | \leq \epsilon |x| or |%DIFDELCMD < {\rm %%% rd (x)-x| \leq \delta which depend linearly on \epsilon and \delta.
In this paper, we provide general bounds on the mean absolute difference and difference of moments of a random variable X and a perturbation rd (X), when | %DIFDELCMD < {\rm %%% rd \mathbf{E | \leq \epsilon |x| or |%DIFDELCMD < {\rm %%% rd (x)-x| \leq \delta which depend linearly on \epsilon and \delta.