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In 5 , we have seen that maximizing likelihood functions or minimizing least squares criteria with respect to parameters of expectation models usually results in a nonlinear optimization problem that cannot be solved in closed form. Therefore, it has to be solved by iterative numerical optimization. In this chapter, numerical optimization methods are discussed suitable for or specialized to such optimization problems. The relevant literature is vast and an exhaustive discussion is outside the scope of this book. Therefore, the discussion will be limited to a relatively small number of methods that have been found to solve the majority of the relevant practical parameter estimation and optimal design problems. Since maximizing a function is equivalent to minimizing its additive inverse, minimization methods discussed below are equally suitable for maximization and the converse. The outline of this chapter is as follows. In Section 6.2, mathematical concepts basic to optimization are presented and their use in numerical optimization is explained. Also, reference log-likelihood functions and reference least squares criteria used for software testing are introduced. Section 6.3 is devoted to the steepest descent method. This is a general function minimization method. It is not specialized to optimizing least squares criteria or likelihood functions. The method converges under general conditions, but its rate of convergence may be impractical. This is improved by the Newton minimization method discussed in Section 6.4. This is also a general function minimization method, but the conditions for convergence are less general than those for the steepest descent method. In Section 6.5, the Fisher scoring method is introduced. This method is an approximation to
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Packaging is only a small part of the market for polyvinyl chloride (PVC), which has seen declining market share in packaging over the last decade or so. PVC packaging in U.S. municipal solid waste is predominantly in the other packaging category (Fig. 4.10), especially in the form of trays and blister packaging. These are used in a variety of applications, including wide use in medical packaging. The properties of PVC packaging can be manipulated to a very wide degree by plasticization. Therefore, PVC packaging ranges from relatively stiff and brittle containers to very soft exible lm used for wraps. In general, PVC is a highly transparent material, with some tendency to yellow over time, especially if it is
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In traditional ePR the textual base requires using pointers to locate and retrieve relevant patient data from many connected information systems, be these systems very small and low end or very large and sophisticated. The data extracted are usually small les without images. Nevertheless, the characteristic textual ePR requires very complex software even though the system interfacing devices, storage, data communication, and hardware requirements are minimal compared to those of PACS and imaging informatics data. When ePR is integrated with imaging data, that, of course, raises the complexity of the ePR in that software requirements of the system s interfacing devices; storage, data communication, and imaging hardware become more demanding. For this reason, after the development of textual-based ePR, many years passed before technologies could catch up to integrate ePR with
< xml version= 1.0 > <html xmlns:xsl= http://www.w3.org/1999/XSL/Transform xsl:version= 1.0 > <head></head> <body> <xsl:apply-templates select= /page/ROWSET/ROW/ENAME /> </body> </html>
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Figure 11-11: The Layer States Manager dialog box. 4. Click New and type a name for your layer state in the New Layer State Name text box of the New Layer State to Save dialog box. If you want, type a description. Click OK. 5. Back in the Layer States Manager, choose the layer states and properties that you want to save in the Layer Settings to Restore section.
The key principle in both approaches is that relationships to stated references are established and that this is done through an unbroken chain of comparisons Practically, this means that the analytical procedure is rst described as a chain or a ow diagram (step 2 in ISO de nition; steps 1 and 2 in Eurachem/CITAC de nition) The word unbroken means that there is no loss of information when considering the different steps in the analytical procedure leading to the measurement result Each step in the procedure then needs to be linked to a reference method, a reference material, or a SI unit (step 1 in ISO de nition; step 5 in Eurachem/CITAC de nition) [12, 24, 27] Figure 4 depicts the successive classes of stated references (materials or methods) in a so-called traceability chain.
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