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aggregation process in parameter estimation

aggregation process in parameter estimation - MC

the treatments are significant. In contrast, the idea behind running an aggregation process is to get an improvement index, indicating how much better one treatment is than the other. Therefore, aggregation methods should be classed as parameter estimation methods rather than hypothesis testing methods, even though their results. More

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Kinetic parameter estimation for cooling

2020-6-1  In this paper, a cell average technique (CAT) based parameter estimation method is proposed for cooling crystallization involved with particle growth, aggregation and breakage, by establishing a more efficient and accurate solution in terms of the automatic differentiation (AD) algorithm.

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Aggregation of AR(2) Processes

2006-4-24  Aggregation of AR(2) Processes DIPLOMARBEIT ... Technische Universit¨at Graz. Abstract We consider the least square estimators of the classical AR(2) process when the underlying variables are aggregated sums of independent random coeffi- ... random coefficient AR(2), least square, aggregation, parameter estimation, central limit theorem 1 ...

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Optimal Parameter Estimation of Conceptually-Based ...

Claps P., Murrone F. (1994) Optimal Parameter Estimation of Conceptually-Based Streamflow Models by Time Series Aggregation. In: Hipel K.W., McLeod A.I., Panu U.S., Singh V.P. (eds) Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Water Science and

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Evaluation of Parameter Estimation Methods for ...

2015-2-1  The process model describes a well mixed, seeded batch cooling crystallization process of a model active pharmaceutical ingredient (API) from a model solvent.A schematic draft of this simplified process is shown in Fig. 1.Initially the seed crystals are suspended in a saturated solution composed of the solvent and dissolved API.If the solubility of the API increases with the temperature, the ...

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Par ameter estimation of coupled w ater and energy

2019-9-12  the rainfall process at different levels of aggregation includ- ing the probability of dry periods and other related proper- ties. Similar changes to the Neyman-Scott rectangular pulses model are introduced in this paper. A practical feature of the models described above is the efficiency of their parameter estimation procedures. Sensi-

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Chapter 4 Parameter Estimation - University of California ...

2012-11-6  turn to basic frequentist parameter estimation (maximum-likelihood estimation and correc-tions for bias), and finally basic Bayesian parameter estimation. 4.1 Introduction Consider the situation of the first exposure of a native speaker of American English to an English variety with which she has no experience (e.g., Singaporean English), and the

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用 Bootstrap 进行参数估计大有可为 - 知乎 - Zhihu

2019-7-25  1 从 t 分布说起 在量化投资领域,有大量需要进行参数估计(parameter estimation)的场景。比如在按照马科维茨的均值方差框架配置资产时,就必须计算投资品的收益率均值和协方差矩阵。很多时候,对于需要的统计量

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GHG Protocol guidance on uncertainty assessment in

2019-12-31  Short Guidance for Calculating Measurement and Estimation Uncertainty for GHG Emissions other parameters) used as inputs in an emission estimation model. Two types of parameter uncertainties can be identified in this context: systematic and statistical uncertainties. Systematic uncertainty occurs if data are systematically biased. In other ...

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Optimal Parameter Estimation in Activated Sludge Process ...

2020-9-18  Optimal Parameter Estimation in Activated Sludge Process Based Wastewater Treatment Water ( IF 2.544) Pub Date : 2020-09-17, DOI: 10.3390/w12092604 Xianjun Du, Yue Ma, Xueqin Wei, Veeriah Jegatheesan Activated sludge models (ASMs) are often used in the simulation of the wastewater treatment process to evaluate whether the effluent quality parameters of a wastewater treatment plant

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A Monte Carlo EM Algorithm for the Parameter

2020-1-20  A Monte Carlo EM Algorithm for the Parameter Estimation of Aggregated Hawkes Processes. 01/20/2020 ∙ by Leigh Shlomovich, et al. ∙ Imperial College London ∙ 0 ∙ share . A key difficulty that arises from real event data is imprecision in the recording of event time-stamps.

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Aggregation Process for Software Engineering

2017-11-21  the treatments are significant. In contrast, the idea behind running an aggregation process is to get an improvement index, indicating how much better one treatment is than the other. Therefore, aggregation methods should be classed as parameter estimation methods rather than hypothesis testing methods, even though their results

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Modelling of the aggregation process using the

2020-6-24  This work presents modelling for the aggregation process of metal nanoparticles following a theory proposed in literature. In this theory, metal atoms aggregate into particles of bigger size due to Van der Waal’s forces of attraction. Then, owing to the electrostatic forces of repulsion, the particles eventually stop aggregating and become stabilized.

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Parameter estimation of Neyman Scott processes for ...

The role of the data aggregation scale on parameters estimation of the cluster-based Neyman-Scott point processes applied to rainfall simulation is investigated. Extensive calculations showed that in estimating the parameters by the method of moments the choice of the aggregation scale of the data significantly affects the estimates of the continuous process parameters.

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APPROXIMATION AND PARAMETER ESTIMATION

2020-11-29  Aggregation processes are intrinsic to many biological phenomena including sedimentation and coagulation of algae during bloom periods. A fundamental but unresolved problem associated with aggregate processes is the determination of the “stickiness function,” a measure of the ability of particles to adhere to other particles.

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Temporal Aggregation Bias and Mixed Frequency

2016-1-26  Estimation of a New Keynesian model (Job Market Paper) Tae Bong Kim This version : Nov 9, 2010 Abstract This paper asks whether frequency misspeci–cation of a New Keynesian model re-sults in temporal aggregation bias of the Calvo parameter. First, when a New Keyne-sian model is estimated at a quarterly frequency while the true data generating ...

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Measurement Error and Time Aggregation

2001-9-12  time aggregation while the elasticity of output with respect to average hours of work increases.Section 4 considers the time aggregation effect explicitly and reports Monte-Carlo simulations showing thatthere is a bias in the aggregation process that explains the results obtained here and in the literature.The estimation bias of theoutput-

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GHG Protocol guidance on uncertainty assessment in

2019-12-31  Short Guidance for Calculating Measurement and Estimation Uncertainty for GHG Emissions other parameters) used as inputs in an emission estimation model. Two types of parameter uncertainties can be identified in this context: systematic and statistical uncertainties. Systematic uncertainty occurs if data are systematically biased. In other ...

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GitHub - AsafGazit/HDTW: Hierarchical aggregation

Hierarchical aggregation process for Dynamic Time Warping (HDTW) which allows DTW-like processes for 2^n input signals while maintaining similar DTW process outputs - AsafGazit/HDTW

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Semi-parametric estimation of the variogram scale ...

2021-6-3  SEMI-PARAMETRIC ESTIMATION OF THE VARIOGRAM SCALE PARAMETER OF A GAUSSIAN PROCESS WITH STATIONARY INCREMENTS Jean-Marc Aza s 1, Franc˘ois Bachoc , Agn es Lagnoux 2,* and Thi Mong Ngoc Nguyen3 Abstract. We consider the semi-parametric estimation of the scale parameter of the variogram of a one-dimensional Gaussian process with known smoothness.

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APPROXIMATION AND PARAMETER ESTIMATION

2020-11-29  Aggregation processes are intrinsic to many biological phenomena including sedimentation and coagulation of algae during bloom periods. A fundamental but unresolved problem associated with aggregate processes is the determination of the “stickiness function,” a measure of the ability of particles to adhere to other particles.

More

Parameter estimation of Neyman Scott processes for ...

The role of the data aggregation scale on parameters estimation of the cluster-based Neyman-Scott point processes applied to rainfall simulation is investigated. Extensive calculations showed that in estimating the parameters by the method of moments the choice of the aggregation scale of the data significantly affects the estimates of the continuous process parameters.

More

OPTIMAL PARAMETER ESTIMATION OF CONCEPTUALLY

2014-7-27  OPTIMAL PARAMETER ESTIMATION OF CONCEPTUALLY-BASED STREAMFLOW MODELS BY TIME SERIES AGGREGATION P. CLAPS1 and F. MURRONE2 1Dept of Environm. Engineering and Physics, University of Basilicata Via della Tecnica, 3 Potenza 85100 - Italy 2Dept Hydraul., Wat. Resour Manag. and Environm. Eng. Univ. of Naples "Federico II"

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Measurement Aggregation and Routing Techniques for

2021-6-14  Measurement Aggregation and Routing Techniques for ... this version: Iordanis Koutsopoulos, Maria Halkidi. Measurement Aggregation and Routing Techniques for Energy-Efficient Estimation in Wireless Sensor Networks. WiOpt’10: Modeling and Optimization in Mobile, ... the task of estimating an unknown parameter or process

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Temporal Aggregation Bias and Mixed Frequency

2016-1-26  Estimation of a New Keynesian model (Job Market Paper) Tae Bong Kim This version : Nov 9, 2010 Abstract This paper asks whether frequency misspeci–cation of a New Keynesian model re-sults in temporal aggregation bias of the Calvo parameter. First, when a New Keyne-sian model is estimated at a quarterly frequency while the true data generating ...

More

Measurement Error and Time Aggregation

2001-9-12  time aggregation while the elasticity of output with respect to average hours of work increases.Section 4 considers the time aggregation effect explicitly and reports Monte-Carlo simulations showing thatthere is a bias in the aggregation process that explains the results obtained here and in the literature.The estimation bias of theoutput-

More

GHG Protocol guidance on uncertainty assessment in

2019-12-31  Short Guidance for Calculating Measurement and Estimation Uncertainty for GHG Emissions other parameters) used as inputs in an emission estimation model. Two types of parameter uncertainties can be identified in this context: systematic and statistical uncertainties. Systematic uncertainty occurs if data are systematically biased. In other ...

More

Semi-parametric estimation of the variogram scale ...

2021-6-3  SEMI-PARAMETRIC ESTIMATION OF THE VARIOGRAM SCALE PARAMETER OF A GAUSSIAN PROCESS WITH STATIONARY INCREMENTS Jean-Marc Aza s 1, Franc˘ois Bachoc , Agn es Lagnoux 2,* and Thi Mong Ngoc Nguyen3 Abstract. We consider the semi-parametric estimation of the scale parameter of the variogram of a one-dimensional Gaussian process with known smoothness.

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The pitfalls in fitting GARCH processes

2001-12-1  procedure of the parameters. A first parameter, fixing the volatility of the process, is computed by a moment estimate. In a second step, the remaining parameters are fitted using a log likelihood method, which allows for a robust estimation framework. This paper is organized as follows: in section 2, the GARCH(1,1) process equations are ...

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[1806.03135] Semi-parametric estimation of the

2018-6-8  Abstract: We consider the semi-parametric estimation of a scale parameter of a one-dimensional Gaussian process with known smoothness. We suggest an estimator based on quadratic variations and on the moment method. We provide asymptotic approximations of the mean and variance of this estimator, together with asymptotic normality results, for a large class of Gaussian processes.

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Aggregation of Space-Time Processes

2010-11-4  Aggregation of Space-Time Processes ... factors will dominate the process for the aggregate, even though they might be relatively unimportant at the individual level. It follows that there might be a bene fitinforecasting ... realistic setting where parameter estimation uncertainty is present. Section 5

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(PDF) On Decomposition and Aggregation Error in

(14) have suggested that "the parametric sensitivity of a more detailed model and its potential to propagate errors may mask the underlying contrast in the data and create problems for parameter estimation."By contrast, the reverse is likely to be true in multiplicative models (e.g., for estimating the frequency of a sequence of events).

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Parameter estimation of Neyman Scott processes for ...

The role of the data aggregation scale on parameters estimation of the cluster-based Neyman-Scott point processes applied to rainfall simulation is investigated. Extensive calculations showed that in estimating the parameters by the method of moments the choice of the aggregation scale of the data significantly affects the estimates of the continuous process parameters.

More

THE EFFECT OF SMOOTHING PARAMETER IN KERNELS

2020-1-13  Smoothing Parameter Selection in Kernel Aggregation Appropriate selection of the smoothing parameter is often critical to the process of kernel aggregation in kernel density estimation because its performance is based on its right selection. The quality of the estimates in Equation (4) and Equation (6) is measured by the

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Garch Parameter Estimation Using High-Frequency Data

2019-9-26  for parameter estimation. One could derive the parameters of the daily Garch process by es-timation of the Garch process with a five-minute time unit using the time aggregation results of Drost and Nijman (1993). Such an approach runs into problems since it does not take into

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Quantitative dynamics of reversible platelet

2019-4-17  Parameter values of the model were determined by means of parameter estimation techniques implemented in COPASI software. ... level of aggregation as the main parameter, ... that the process

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Measurement Aggregation and Routing Techniques for

2021-6-14  Measurement Aggregation and Routing Techniques for ... this version: Iordanis Koutsopoulos, Maria Halkidi. Measurement Aggregation and Routing Techniques for Energy-Efficient Estimation in Wireless Sensor Networks. WiOpt’10: Modeling and Optimization in Mobile, ... the task of estimating an unknown parameter or process

More

A change in the aggregation pathway of bovine serum ...

2017-6-21  Thus, parameter K LS can serve as a measure of the initial rate of the aggregation process. As expected (see Equation ( 4 )), parameter K LS is a linear function of the initial protein ...

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Semi-parametric estimation of the variogram scale ...

2021-6-3  SEMI-PARAMETRIC ESTIMATION OF THE VARIOGRAM SCALE PARAMETER OF A GAUSSIAN PROCESS WITH STATIONARY INCREMENTS Jean-Marc Aza s 1, Franc˘ois Bachoc , Agn es Lagnoux 2,* and Thi Mong Ngoc Nguyen3 Abstract. We consider the semi-parametric estimation of the scale parameter of the variogram of a one-dimensional Gaussian process with known smoothness.

More

[1806.03135] Semi-parametric estimation of the

2018-6-8  Abstract: We consider the semi-parametric estimation of a scale parameter of a one-dimensional Gaussian process with known smoothness. We suggest an estimator based on quadratic variations and on the moment method. We provide asymptotic approximations of the mean and variance of this estimator, together with asymptotic normality results, for a large class of Gaussian processes.

More