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Short Implants
Takes the reader through their research and development, explain the clinical indications, evaluate the outcomes achieved with various implants, and explore restorative and laboratory considerations. Short implants have steadily gained greater market share in the last decade as practitioners sought alternatives to traditional length implants in order to avoid grafting procedures. Current manufacturers offer a variety of implant lengths and widths, allowing surgeons and restorative dentists the ability to select the best implant for each clinical circumstance. Cutting edge information is provided on the research and clinical results achieved utilizing a range of implants, specifically those developed by Nobel Biocare, Straumann, Jack Hahn, and Bicon. Readers will also find an extensive description of the role of ultra-short implants involving reconstruction in both cleft patients and cancer patients who have lost portions of their mandible and/or maxilla.
Estimation in Conditionally Heteroscedastic Time Series Models
ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic). This monograph concentrates on mathematical statistical problems associated with fitting conditionally heteroscedastic time series models to data. This includes the classical statistical issues of consistency and limiting distribution of estimators. Particular attention is addressed to (quasi) maximum likelihood estimation and misspecified models, along to phenomena due to heavy-tailed innovations. The used methods are based on techniques applied to the analysis of stochastic recurrence equations. Proofs and arguments are given wherever possible in full mathematical rigour. Moreover, the theory is illustrated by examples and simulation studies.
