Producing accurate and reliable project cost estimations at an early stage of a project's life cycle remains a substantial challenge in the information technology field.
Recent methods using incremental estimation approach could alleviate the computational difficulty by performing the parameter estimation one-reaction-at-a-time.
"Minimax Linear Estimation at a Boundary Point", Journal of Multivariate Analysis, 2018, 165, 262-269.
The results indicate that methodologies could be useful for modelers working in the field of soil moisture information system and SMD estimation at a catchment scale.
A new technique is presented in this paper for real single tone parameter estimation at a low computational cost based on the development of a two-bin estimator, and its extension to efficient multiple-bin estimators.
The performance obtained after all those changes indicate that SCA-H using WRF NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.
Furthermore it is shown that the dynamical characteristics of the reactor are such that, by a proper design of the Luenberger observer, the concentration estimation at a given collocation point can be made independently of the estimation at other collocation points.
Overall, the performance of Landsat 8 based ET compared to available EC datasets and water balance estimates for a complex basin such as the CRB demonstrates the potential of using Landsat 8 for annual water use estimation at a national scale.
For this case, the most accurate performance is attained for the ST estimation at a depth of 50 cm, with the highest value of R = 0.992, WI = 0.999, Nash = 0.981, LMI = 0.879 and the lowest value of the relative RMSE and MAE values (i.e., 4.7 and 4.0%, respectively), attained using T-air, W, RH and periodicity as the predictor variables.
Both methods are generalized forms of univariate and multivariate linear regression models, for estimation at a point, over an area, or within a volume.
