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Section 5 briefly presents how we use MDS to find position estimates, discusses the results from applying our algorithms and MDS to the simulated and measured data, and demonstrates the effect of transmitter positions using the simulated data.
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Writer gives various estimates and discusses ways to achieve greater production.
This section presents -estimates, a generalization of maximum likelihood (ML) estimates, and discusses optimal filtering from an ML perspective.
This paper reports on the design and fabrication of a suitable fuel processor having this capability and discusses estimates of the start-up fuel consumption for the laboratory unit.
Section 5 provides a qualitative discussion of the results based on the econometric estimates, while Section 6 discusses their quantitative implications in terms of the number of permanent jobs saved since the start of the global financial crisis.
Section 4 presents and discusses the estimates of the number of workers paid less than the sectoral minimum wages and some robustness tests using alternative data sources.
The chapter also discusses how to estimate the driver requirements.
Section 3 discusses methods to estimate the noise distribution and how to exploit this information for demapping.
The following section discusses how the estimate for m can be gained with information from the GPON network.
Furthermore, it extends Kriging to random simulation, and discusses bootstrapping to estimate the variance of the Kriging predictor.
Section 2 defines the problem of criminal incident modeling formally, describes ST-GAM and LST-GAM in detail, and discusses how to estimate parameters as well as evaluate spatial prediction performance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com