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aggregation process in parameter estimation
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Sparse estimation of parameter support sets for …
larization hyperparameters by choosing parameters having a maximum selection frequency above a certain threshold. Ruiz et al. [2020] considered estimating VAR models by pooling supports meeting optimality criteria across resamples. In this work we propose a sparse estimation method based on simple aggregation oper-
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A data assimilation approach for groundwater parameter estimation …
Spatial heterogeneity in groundwater system introduces significant challenges in groundwater modeling and parameter calibration. In order to mitigate the modeling uncertainty, data assiilation methods have been applied in the parameter estimation by assessing the uncertainties from both groundwater model and …
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[2108.12357] A Parameter Estimation Method for …
Here we generalise existing methodology on parameter estimation of univariate aggregated Hawkes processes to the multivariate case using a Monte Carlo …
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Learning Interacting Particle Systems: Diffusion Parameter Estimation
The inverse problem of parameter estimation in aggregation-diffusion equations is considered in [30], where the diffusion parameter estimation is studied subject to the Newtonian aggregation and ...
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Aggregation (Econometrics) | SpringerLink
The econometrics of aggregation is about modelling the relationship between individual (micro) behaviour and aggregate (macro) statistics, so that data …
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Aggregation Functions
Aggregation is the process of combining several numerical values into a single representative value, and an aggregation function performs this operation. These …
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Quantitative dynamics of reversible platelet aggregation
In the present study, we developed a mathematical model of reversible platelet aggregation which incorporated a novel mechanism of disaggregation, could be used for clinical parameter estimation ...
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Power estimation method of low-voltage distributed …
4.2. Middle-voltage distributed photovoltaic aggregation. According to the middle-voltage distributed photovoltaic aggregation model and aggregation method in Section 2, the 60 middle-voltage photovoltaic generations are divided into three aggregators by K-means method after 2 iterations. The typical power curves of the three aggregators …
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Cost Aggregation
The main benefit of cost aggregation is that it allows the project management team to see scheduled spending for every time period. This will allow project managers to see the activities as well as the corresponding costs. The main output of cost aggregate is the determination of the cost-performance baseline.
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Cost Aggregation
Cost aggregation is the process of adding up the estimated costs of individual work packages or activities within a project to determine the total project budget. This process typically occurs during the planning phase of project management and requires breaking down the project into work packages or activities to estimate and allocate resources.
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(PDF) A Parameter Estimation Method for Multivariate
Here we generalise existing methodology on parameter estimation of univariate aggregated Hawkes processes to the multivariate case using a Monte Carlo …
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Fitting functional responses: Direct parameter estimation …
This equation is commonly used to estimate parameter values for a type II functional response when prey depletion occurs, and we refer to it as Rogers' Random Predator Equation II (RRPE-II). With the unknown number eaten N e appearing on both sides of this implicit equation (RRPE-II), the problem arises that a simple nonlinear fitting ...
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Selection of optimal aggregation function for the revised
A tool to quantify the pollution potential of leachate, termed the revised leachate pollution index (r-LPI), has been developed. It was developed using the fuzzy Delphi analytic hierarchy process (FDAHP). The formulation entails four major steps: parameter selection, weight calculation, normalization of parameters, and aggregation …
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Estimation of aggregation kernels based on Laurent …
The dynamics of the aggregation process described by Eq. (3) are governed by the aggregation kernel k, which is assumed to be independent of time.The aim of this work is the estimation of this kernel. For developing and assessing the estimation procedure described below, we use three different kernel functions which are given in …
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Optimal experiment design: Link between the
The overwhelming majority of studies dealing with determination of aggregation parameters from experimental titration curves, do not bother with optimal experiment design. As a consequence, the experimental setup is typically determined by other factors than the required optimum for the most accurate estimation of the search …
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Adjustable discretized population balance equations: …
Considering fractal aggregation and break-up, two major parameters were found to be collision efficiency α of 0.3938 and aggregate break-up coefficient K B of 4.4105 using a parameter estimation scheme coupled with an improved discretized population balance equation. This parameter estimation scheme was able to compute the …
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The effect of temporal aggregation on parameter estimation in
In Tiao and Wei (1976) the authors have considered the exact relationship between a given basic infinite distributed lag model and the corresponding model for temporal aggregates. In this paper we study the effect of temporal aggregation on parameter estimation in the above general finite distributed lag model (1.1).
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Impact of Aggregation and Deterrence Function Choice on the Parameters
2.1 Related Works. The calibration of the gravity model and the impact of level of aggregation has been recently presented in 2016 by Delgado and Bonnel [] they demonstrated using the case of Lyon that the level of zoning which is selected when constructing O–D matrices and calibrating the parameters of the gravity model has a …
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Crowd flow forecasting via agent-based simulations with
The estimation result with the additional parameter for Case 3 is shown in Fig. 9, with the ground truth and the original estimation. The result demonstrated that the additional latent parameter ...
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Bayesian inference for aggregated Hawkes processes
We develop a Bayesian estimation procedure for the parameters of a Hawkes process based on aggre- gated data. Our approach is developed for temporal, spatio-temporal, …
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Sparse estimation of parameter support sets for …
In this work we propose a sparse estimation method based on simple aggregation oper- ations applied to multiple estimates obtained from data resampling, and demonstrate …
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GHG Protocol guidance on uncertainty assessment in …
inventory is the uncertainties associated with parameters (e.g. activity data, emission factors, and 3 The role of expert judgment in the assessment of the parameter can be twofold: Firstly, expert judgment can be the source of the data that are necessary to estimate the parameter. Secondly, expert judgment can help (in combination with
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(PDF) A Parameter Estimation Method for Multivariate
There parameter estimates suggest that for each event in process 1, an average of 0.27 ev ents will be triggered in process 2. The baseline parameters given by ν indicate the rate of the events ...
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A parameter estimation method based on aggregated data
In constructing multiprocessor-based distributed process control systems, one approach is to use low-end processors to carry out direct control tasks …
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Data aggregation processes: a survey, a taxonomy, and …
The aggregation process is defined with a stopping interface, through which the aggregation can be stopped, giving the approximate result as the final result. ... In the Aurora data stream management system, the aggregate function can be associated with a "timeout" parameter, indicating the deadline of the computation of the function. A ...
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Development of new fruit quality indices through aggregation …
After each of the quality parameters was converted into the subindex value, the subindex values of the selected of the quality parameters were combined into a numerical value that indicated the level of fruit quality. In this study, two mathematical equations were used for the aggregation process. 2.4.3.1. Fruit quality index 1 (FQI1)
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Long-term stability predictions of therapeutic monoclonal …
We repeat the parameter estimation and prediction for the desired conditions for each perturbed set to obtain a distribution of predictions. ... The aggregation process ...
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Unbiased parameters estimation and mis-specification
From Tables 2 and 3, it can be observed that the parameters estimation of μ λ and σ B 2 calculated by the direct MLE method and the unbiased parameters estimation method are the same. In most of cases, the MSEs of the unbiased estimators of σ λ 2 are a little worse than the traditional MLE method, especially for small n.This phenomenon is in …
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Full article: Parameter Estimation of Binned Hawkes Processes
Parameter Estimation of Binned Hawkes Pr .... Journal of Computational and Graphical Statistics Volume 31, 2022 - Issue 4. Open access. 2,270. Views. 1. CrossRef citations to …
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Joint estimation and regularized aggregation of brain network …
The latter two approaches are described in 2.1 Joint Estimation of Multiple Precision matrices, 2.2 Regularized aggregation, respectively, and our suggested method is illustrated in Section 2.3. MRI methods were reported in Pierce and McDowell (2017) and described in Section 2.4. 2.1.
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Aggregation parameter
Aggregation parameter A lot of substances and components are present in wastewaters and can be measured, especially the ... (/V-methylpyrolidone) and nitrite can be detected in effluents or process water [21], Moreover, the estimation of complementary aggregate parameters, such as total oxygen demand (TOD), is possible from the estimation of ...
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Capacity estimation of lithium-ion batteries based on data aggregation …
(1) The data aggregation scheme is designed to comprehensively utilize the measurements. (2) The specific aggregation and fusion operations are selected automatically, which avoids the feature engineering. (3) Only partial charging data is adopted, which can be applied under incomplete charging process.
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Review of the current state of protein aggregation inhibition …
Here, native monomers first bind to a surface to initiate the process of aggregation. Next, a conformational change in the monomer (e.g., to increase the contact area with the surface) may occur. The driving forces could be hydrophobic or electrostatic interactions, based on the nature of the surface.