Titlebook: Subsampling; Dimitris N. Politis,Joseph P. Romano,Michael Wolf Textbook 1999 Springer Science+Business Media New York 1999 Resampling.Subs

Cognizance

显而易见

Choice of the Block Size of subsampling methods, the two asymptotic conditions do not give much guidance with respect to how to choose . when faced with a finite sample. The aim of this chapter is to provide some guidelines for this task. It turns out that the optimal choice of . depends on the purpose for which subsampling is used.

传授知识

CHIP

iographic indicators for lateral ankle instability diagnosis are 10 degrees or greater talar tilt, 10 mm or greater anterior drawer, or 5 degrees/5 mm difference from the contralateral side. While the modified Brostrom-Gould repair is the gold standard for lateral ankle instability, confounding fact

残忍

outset

Dimitris N. Politis,Joseph P. Romano,Michael Wolf millions of patients with end-stage arthritis.. It has also revolutionized the surgical treatment of arthritis for the past 30 years. Despite the enormous success of these procedures, however, aseptic loosening of the components—often associated with periprosthetic osteolysis and frequently necessi

松软无力

Dimitris N. Politis,Joseph P. Romano,Michael Wolflmination of a remarkable, mation and armamentarium available, prior their exe­ fertile, and dedicated career in hip surgery by Dr. cution. Roderick H. Turner. Dr. Turner continued, expanded, Several chapters address, in depth, different avenues and advanced the art and science of total hip replace­

分开如此和谐

抗生素

Dimitris N. Politis,Joseph P. Romano,Michael Wolfuntries have led to newer designs and expanding indications, which have resulted in rapid growth around the world. Despite numerous advances in surgical techniques and implant designs, however, complications still occur, and with an active aging population and increasing popularity among upper extre

朴素

Subsampling Marked Point Processesandom variables .(.) taking values in an arbitrary state space ., and indexed by the continuous variable t ∈ ℝ.. However, for reasons to be apparent shortly, the probability law of the random field {X(.), . ∈ ℝ.} will be denoted by . (and not .) throughout this chapter.