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The iteration is terminated when the norm of the difference between two successive spatial estimates is smaller than a certain threshold.
Observe that the variance of these location estimates is smaller when K=5; this is due to the fact that Prony's method and its variations are more robust to noise when K is large.
Similar qualitative results have been reported in the related literature (Ettner 1995; Heitmueller and Michaud 2006; Heitmueller 2007), although the size of our estimates is smaller than the estimates of Heitmueller (2007) and Heitmueller and Michaud (2006), who analyse British women within similar age ranges.
For all the numerical examples below, we adopt the stop criterion that halts the iterative BLUE if either Γ[k], which is defined in (19) as the normalized difference in energy between the previous and current estimates, is smaller than 10-6 or the number of iterations K is higher than 30.
Hoerl and Kennard (1970) showed that there is a range of γ values where the mean squared error (MSE) of estimates is smaller than the corresponding MSE of the ordinary least squares solution.
Similar(55)
For small lags, the variance of the estimates is small, but the estimation is highly biased.
The amount of material involved in these estimates is small, but can be used to generate powerful results.
This was accompanied by very large confidence intervals around I2, even for the comparisons where heterogeneity estimates were smaller.
However, the variances of the model-assisted and model-based estimates were smaller compared to those of the design-based method.
All proportion forest cover estimates were similar, but the variances of the MAR estimates were smaller than variances for the direct expansion estimates by factors as great as 50.
However, with the cubic interpolation, the percentage error of the estimates was smaller.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com