Sentence examples for estimator bar from inspiring English sources

In our estimation of the induced relative risk, we used an improved estimator (bar {phi }_{j}(beta,t)) for (jin bar {V}).

For each given value of β, with the estimator (bar {nu }_{j}(beta,t)), we can estimate the induced relative risk r i (β,t) in (3.4) by hat{r}_{i}(beta,t)=eta_{i}gamma_{i}(beta,t) + 1-eta_{i} bar{phi}_{i}(beta,t), (3.9).

Now, consider a new estimator, (bar {hat {h}}_{n}), which is the average of all estimates until time slot n.

Of course, the natural way to approximate Y t and Z t is to estimate first the unknown parameter 𝜗 with the help of some estimator (bar {vartheta }) and then to put, say, ({bar {Y}}_{t}=u(t,X_{t},{bar {vartheta }}) ).

We must understand what the conditions imposed on the estimator (bar {vartheta }) that allow us to say that it is good.

The updated estimator (bar {nu }_{j}(beta _{1},t)) is doomed to be more accurate than (hat {nu }_{j}(beta _{1},t)) in (3.5), since it has used the information from W and observations in (bar {V}).

We formulate the maximum likelihood (ML) estimator of (bar {lambda }_{t}) given the N observations ({k_{tn}}^{N}_{n=1}) as [29] hat{lambda}_{ML}(t) longrightarrow underset{bar{lambda}_{t}}{argmax},, left(prodlimits_{n=1}^{N} text{e}^{-bar{lambda}_{t}}frac{(bar{lambda}_{t})^{k_{tn}}}{k_{tn}!}right), (52).

For boxplots and kernel density estimator, the central bar is the median; the upper and lower bars are at quartiles.

An arbitrary estimator ({bar {Z}}_{t}) of Z t we write as ({bar {Z}}_{t}=varepsilon tilde Z_{t}).

Recall that the vector-process (X s,0≤s≤T) converges uniformly in s to the deterministic vector-function (x s,0≤s≤T) and the estimator ({bar {vartheta }}_{tau _{varepsilon }} ) is consistent.

Suppose that we have a preliminary estimator ({bar {vartheta }}_{T^{delta }} ) constructed by the observations (X^{T^{delta } }=left (X_{t}, 0 leq tleq T^{delta }right)) with (delta in (frac {1}{2},1]).