A general asymptotic scheme for inference under order restrictions

• Limit distributions for the greatest convex minorant and its derivative are considered for a general class of stochastic processes including partial sum processes and empirical processes, for independent, weakly dependent and long range dependent data. The results are applied to isotonic regression, isotonic regression after kernel smoothing, estimation of convex regression functions, and estimation of monotone and convex density functions. Various pointwise limit distributions are obtained, and the rate of convergence depends on the self similarity properties and on the rate of convergence of the processes considered. © Institute of Mathematical Statistics, 2006.

Ämnesord

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)

NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

Nyckelord

range dependent sequences

monotone regression

density

empirical process

brownian-motion

nonparametric regression

subordination

estimators

sums

convergence

range dependent sequences

monotone regression

brownian-motion

nonparametric regression

empirical process

density

subordination

convergence

estimators

sums

monotone

convex

estimation

dependence

regression function

density estimation

limit distributions

Publikations- och innehållstyp

art (ämneskategori)

ref (ämneskategori)