To check the validity of a parametric model for survival data, a number of supremum-type tests have been proposed in the literature using Khmaladze's (1993, Ann. Statist. 18, 582-602) transformation of a test process. However, such a transformation is usually very complicated and lacks a clear inter
Slice sampling for simulation based fitting of spatial data models
β Scribed by Deepak K. Agarwal; Alan E. Gelfand
- Publisher
- Springer US
- Year
- 2005
- Tongue
- English
- Weight
- 133 KB
- Volume
- 15
- Category
- Article
- ISSN
- 0960-3174
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## Abstract A statistical interpolation technique is presented for modeling Sβparameter measurements for use in statistical analysis and design of circuits. This is accomplished by interpolating among the measurements in an Sβparameter data base in a statistically valid manner.
We present numerical results illustrating the successful state feedback control of a spatially developing boundary-layer ow system. Control is applied using the noncausal framework developed in Part I of this study. After addressing some important regularization issues related to the proper treatmen