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The statistical properties of estimated models are studied with respect to input signals and possible sensor locations.
We continue the exploration of properties of estimated components, including how they differ from properties of the unobserved components, now for the ARIMA case, using the (q=2) SRW 3-component decomposition.
First, the properties of estimated breeding values (EBV) were investigated using 1000 replicated schemes without selection.
The purpose of the simulation was to study properties of estimated breeding values from the BER and BB methods, and to compare the estimated breeding values.
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The general properties of estimates, e.g. a small bias of estimation from both methods in the noninbred population and a downward bias of in the inbred population, were similar to those observed in Figs 1– 3. A remarkable point in Table 2 is a narrower confidence interval of in a small sample of progeny from a small inbred population.
We begin our autocorrelation-based consideration of the smoothing properties of estimates.
The properties of estimates and stopping time are obtained under the proposed stopping rule.
Spatiotemporal variation and statistical properties of estimates of the parameters (including the mean, standard deviation, and coefficient of skewness) of standardized flows are shown in Fig. 8.
Second, a simulation study was carried out to compare the statistical properties of estimates based on the use of PVs with those based on other, commonly used methods.
Next, we discuss briefly the effects of shrinkage on the statistical properties of estimates and subsequently review some of the most commonly used penalized and Bayesian variable selection and shrinkage estimation procedures.
We compare this model to normalized reverse correlation (NRC), the traditional method for STRF estimation, in terms of predictive power and the basic tuning properties of the estimated STRFs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com