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Probabilistic estimate of the random time interval for the existence of a local solution is expressed in terms of expected values of the initial data and the random noise.
Thus, model results may appear more robust than they really are because they fit with equal felicity both a theoretical pattern underlying the data and the random noise buried within it (Cutting, 2000; Pitt & Myung, 2002).
Results show that the proposed approaches properly identify the random field model (including μ, σ, λ, and M⁎) of φ′ using project-specific CPT data, and the random field parameters of φ′ depend on the correlation function used to interpret CPT data.
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For books with large popularity, the empirical data and the random-node case become closer.
When the user enters a password, the TMZ system generates the signature data and sends the random data and the signed random data to the authentication server.
The Pearson-type residuals from the adopted final model were plotted against the observed responses and the predicted responses (the latter computed on the scale of the data and incorporating the random effects).
The long-term simulation produced mean data and smoothed the random variations in each parameter tested, leading to the identification of two distinct phases during the active period of the rat: the restoration and the maintenance.
These small p-values indicated the significant difference between our data set and the random cases.
The distribution of r's between our data set and the random case (see Methods for a derived closed form solution of the random case) clearly differed (Figure 1A).
SAS, Version 9.1, was applied for all data analyses and the random number generation.
We assessed the significance of PLV with 2 different surrogate methods: one is based on random shuffling of data and the other on random resampling of data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com