%0 Journal Article %1 Pal2008 %A Pal, Jayanta Kumar %D 2008 %J Statistics and Probability Letters %K LeastSquares Regression:isotone Regression:monotonicity Spiking %N 12 %P 1548-1556 %R 10.1016/j.spl.2008.01.015 %T Spiking problem in monotone regression: Penalized residual sum of squares %U http://dx.doi.org/10.1016/j.spl.2008.01.015 %V 78 %X 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.

@article{Pal2008, abstract = {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.}, added-at = {2014-04-07T16:33:31.000+0200}, author = {Pal, Jayanta Kumar}, biburl = {https://www.bibsonomy.org/bibtex/223e954c37cac57b9042760979365d1fa/marsianus}, doi = {10.1016/j.spl.2008.01.015}, interhash = {0b647d4a8116e3898f0cb444b4b91f7e}, intrahash = {23e954c37cac57b9042760979365d1fa}, journal = {Statistics and Probability Letters}, keywords = {LeastSquares Regression:isotone Regression:monotonicity Spiking}, number = 12, pages = {1548-1556}, timestamp = {2014-06-26T11:21:34.000+0200}, title = {Spiking problem in monotone regression: Penalized residual sum of squares}, url = {http://dx.doi.org/10.1016/j.spl.2008.01.015}, volume = 78, year = 2008 }