Spiking problem in monotone regression: Penalized residual sum of squares

We consider the estimation of a monotone function at its end-point, where the least square estimate is inconsistent. The least square criterion is penalized to achieve consistency. The limit distribution for the residual sum of squares is derived, to construct confidence intervals.