Sentence examples for average estimator from inspiring English sources

More generally, we have not explicitly compared the moving average estimator with the spline-fit or loess-based techniques to estimate the standard deviation used in other studies (see Background).

but is the bias the difference between the function and the average estimator?

We compared three load estimation methods (the 7-parameter regression estimator, the ratio estimator, and the flow-weighted average estimator) applied at 1, 2, 4, 6, and 8-week sampling frequencies and 1, 2, 3, and 6-year monitoring durations.

By (H1 - H2), the MSE of the weighted average estimator is given by.

Denote ĝ n ( b ) ( t ) be the b th estimator of g(t) under the size n, and ĝ ̄ n ( t ) = ∑ b = 1 B ĝ n ( b ) ( t ) ∕ B be the average estimator of g(t).

On the one hand, similar to Theorem 2.1, Hansen [12] investigated the kernel average estimator widehat{Psi}(x)=frac{1}{n}sum_{i=1}^{n}Y_{i}K_{h} x-X_{i}), and obtained the variance bound (operatorname{Var} x-X_{i}{Psi}(x))leq frandTheta}{nh^{d}}), where Θ is a pobtainedconsthet.

Figures 1 and 2 respectively provide the average estimators of the nonparametric function g and RMSE n values for Cases I and II, respectively.

A simple type of window-based ARP estimators, namely weighted sample average estimators of local mean power, is currently deployed in many commercial communication systems, and various other window-based estimators (WBEs) have been proposed in [21].

While the average components, <BLC>, for the random set are almost zero, those of the observed wind vectors show the expected bias, low bias to A and S and high bias to W. The rest of the average estimators described in the Table 4 (<σ>, <dist> and <α>) confirms the less dispersion of the observed data with respect to a random vector set.

This approach has the limitation that the bias of the averaged estimator depends only on N. Hence, if N is relatively small, the bias is large even if we use a very high number M of parallel filters.

The ensemble approximation of π t with M independent filters is the discrete random measure (pi _{t}^{M times N}) constructed as pi_{t}^{M times N} = frac{1}{M} sum_{m=1}^{M} pi_{t}^{m,N}, and the averaged estimator of (f,π t ) is (left (f,pi _{t}^{Mtimes N}right)).