generalized branch predictorgshareA generalized branch predictor is proposed in this paper. This predictor is a general case of most of the predictors used nowadays, including One-Level Predictor, Two-level predictor, Gshare, and all their close and distant variations. Exact pros and cons of ...
Tree height to crown base (HCB) is defined as the height from the ground to the base of the first normal green branch as a part of the crown; this excluded secondary branches (epicormic and adventitious) (Hasenauer and Monserud, 1996). Measuring HCB is necessary for estimating tree CR, ...
We demonstrate that although the topology of the viral phylogenies was consistent across analyses, support for the predictors depended on the level of aggregation. In particular, we found that the variance of the predictor support metrics was minimized at the most precise level for several predictors...
Better to construct a physic-economic model, but very hard to do. The true predictor is in the ensemble mean that is achievable from the "peak oil update" section. What about updating it? Update the peak oil update, please!Curious...
A generalized branch predictor is proposed in this paper. This predictor is a general case of most of the predictors used nowadays, including One-Level Predictor, Two-level predictor, Gshare, and all their close and distant variations. Exact pros and cons of different predictors are clearly ...
We conducted two simulation studies; the first compared the performances of three test statistics, the score, the Wald, and the LRT; and the other compared the performances of model selection through forward selection, AIC, and BIC. Empirical level and power of the score, the Wald, and the ...
The mean of the response variable is then linked to the linear predictor through the logit function, i.e., log μ i m − μ i = x i T β . Table 4 presents the estimated coefficients of the regression vector for the carrots data using the MLE and robust MRPEs when the model ...
This represents the ratio of the odds that mortality will occur given the presence of different levels of the predictor variables against the control group (𝐹6F6). The odds ratio of mortality comparing to the fungicide 𝐹6F6 is expressed by Equation (2): 𝑂𝑅𝐹𝑗=exp(𝛽𝐹𝑗...
,𝜃𝑝) is a p-dimensional vector of unknown parameters, where a linear predictor, ξ i = x i ⊤ θ 𝜉𝑖=𝐱⊤𝑖𝜽, is obtained for i = 1 , 2 , … , n 𝑖=1,2,…,𝑛. Then, let us suppose that T 1 , T 2 , . . . T n 𝑇1,𝑇2,...𝑇𝑛 are...
In the first stage, we can apply point-biserial correlation as a marginal index to check the correlation between each predictor and the response to reduce the dimension of the data to a moderate size. Then, we apply a regularization method to further select important predictors and build the ...