is underlined).

Looking at the MISE, it turns out that the estimator using the Cramér-von Mises distance (TCM) out-performs in many cases even when it does not out-perform the mean; see Tables \[Table1\] and \[Table2\] when $n=100$ for instance. Besides, as it is intented, results are better in most of the cases when the sample size $n$ increases. However, this does not hold for every case. For instance, one may see in Table \[Table2\] that for the second estimator TCM, most of the results are better for $n=50$ than for $n=100$. This might relate to a sensitivity with respect to the choices of bandwidth and smoothing parameter. A lot of criteria may be used to judge the performance of the estimators. We deal here with the mean, the median and the MISE but we emphasize that using different criteria (e.g. median absolute deviation, mode or even graphical analysis) could give different results concerning the comparison of the methods. For instance, results in Table \[Table7\] for $n=100$, $a_n=b_n/2$ and $\t_0=1$ are quite not accurated regarding the mean (e.g. $0.845$ for the TCM). Nevertheless, looking at Figure \[est2\], it appears that the plots of the densities look satisfactory.

It is clear that 