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Our observation helps in estimation and modeling the effects of climate change along the boreal biogeographical zones.
In this paper, we propose an artificial neural-network-based approach for software reliability estimation and modeling.
Hence, friction force estimation and modeling in CNC machine guideways is used to overcome these problems by controlling the lubrication operation.
By incorporating prior biological knowledge, utilizing advanced statistical method for parameter estimation and modeling unobserved nodes as latent variables, we developed a novel approach to infer active signaling networks from experimental data and a canonical network.
The R Language and Environment for Statistical Computing (release 2.11.1) [ 35] and the "periodR" package (release 1.0-6) were used for the data preparation, survival estimation and modeling [ 36, 37].
Clearly, we cannot apply these methods to large numbers of people, but collection of such data even on small subsamples of the population will provide valuable additional information, for example, on within-area variability of both the exposure data and potential confounders, which will help improve the exposure estimation and modeling (Jackson et al. 2006).
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We are also grateful for Paul Dickman (Associate Professor of Biostatistics in Karolinska Institute) for his support during regarding relative estimation and modelling.
Limitations with the AMOS software did not allow for the use of appropriate sampling weights for estimations and modeling.
For instance, the works [28 32] tackle state estimation and model fitting problems jointly.
The relationship with other design procedures for parameter estimation and model discrimination is discussed.
A simulation experiment illustrates good performance in estimation and model selection over reasonable sample sizes.
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