Parameter estimates for fitted ACD models (IBM data)
Data-driven Simple Thermal Models: The Importance of the Parameter Estimates
... the parameter estimation for a simple thermal model for buildings from a ‘building physics’ perspective, to ensure that the model will eventually be less dependent on (although driven by) the monitored data, ...
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Data-driven simple thermal models: the importance of the parameter estimates
... the parameter estimation for a simple thermal model for buildings from a ‘building physics’ perspective, to ensure that the model will eventually be less dependent on (although driven by) the monitored data, ...
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Parameter redundancy and the existence of maximum likelihood estimates in log linear models
... Log-linear models are typically fitted to contingency table data to de- scribe and identify the relationship between different categorical ...is parameter redundant for a pattern of observed zeros in ...
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High Frequency Data: Modeling Durations via the ACD and Log ACD Models
... initial parameter estimates in the Log ACD 1 model for use in recursive ...Log ACD 1 model to find recursive estimates for the unknown parame- ters in the ...the ACD and Log ...
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The Influence of Sample Size on Parameter Estimates in Three-Level Random-Effects Models
... longitudinal models, it is often unclear which sample size is necessary for reliable parameter ...effects estimates, whereas higher-level random effects variance estimates require larger ...
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Conditional parameter estimates from Mixed Logit models: distributional assumptions and a free software tool
... So far, we have looked at the empirical distribution function for the condi- tional means across respondents, and have compared these distributions across the five models. What is also interesting is to look at ...
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Conditional parameter estimates from Mixed Logit models: distributional assumptions and a free software tool
... distributions, while, for the time coefficient, the ranges are more comparable. So far, we have looked at the empirical distribution function for the condi- tional means across respondents, and have compared these ...
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Globally optimal parameter estimates for nonlinear diffusions
... as models for random phenomena that evolve continuously in ...deterministic models described by ordinary differential ...likelihood estimates is difficult, primarily because it is usually impossible ...
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Inverse transformed encoding models - A solution to the problem of correlated trial-by-trial parameter estimates in fMRI decoding
... trial-by-trial parameter estimates, termed inverse transformed encoding modelling ...trial-wise parameter estimates, as implied by the trial-wise design matrix that is used to generate ...
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Use of Bayesian Estimates to determine the Volatility Parameter Input in the Black-Scholes and Binomial Option Pricing Models
... pricing models to price options remains ...binomial models might be improved, while still retaining their essential ...sophisticated models that have been ...
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Modelling Intraday Trading Activity Using Box-Cox-ACD Models
... of ACD models, based on Box-Cox transformations of the conditional mean function, have been ...that ACD models based on flexible conditional mean functions provide the best fit of the data as ...
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Genetic parameter estimates for birth and weaning weights in Raeini goats
... 2 Department of Animal Science, Aburaihan College of Agricultural Science, Tehran University, Tehran, Iran 3 young Researchers Club, Islamic Azad University, Islamshahr Branch, Teheran, Iran AbstRAct: The aim of the ...
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Genetic parameter estimates for weaning weight and Kleiber ratio in goats
... three models (Model 1: without maternal genetic effect, Model 2: with maternal genetic effect and am = 0, and Model 3: with maternal genetic effect and am 0) were used to estimate genetic parameters for this ...
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Bayesian estimates of parameter variability in the k − ε turbulence model
... Within the framework of RANS, many turbulence models are available, see e.g. Ref. 5 for a review. There is general agreement that no universally-”best” RANS turbulence closure model is currently known; the ...
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A Parameter-Uniform Essentially First Order Convergent Fitted Mesh Method for a Singularly Perturbed Robin Problem
... to parameter-uniform numerical methods for singular perturbation problems, see [1],[2],[3] and ...asymptotic estimates of solutions of the singularly perturbed Robin problem for the general nonlinear ...
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Parameter identifiability of fundamental pharmacodynamic models
... successful parameter estimation and practical parameter ...true parameter values, followed by re-estimation of the parameter ...to parameter estimation can improve the parameter ...
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On parameter orthogonality in symmetric and skew models
... likelihood estimates were found by solving the likelihood equations using the nleqslv package in R (Hasselman, 2009) and checking negative definiteness of the Hessian ma- ...
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Removing the stabilization parameter in fitted and unfitted symmetric Nitsche formulations
... stabilization parameter, this has not been considered for Nitsche formulations in other ...a parameter-free variant for two applications of Nitsche’s ...with fitted meshes and secondly, an unfitted ...
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United Kingdom Maritime Pilot s Association. Piloting Vessels Fitted With Azimuthing Control Devices (ACD s)
... This booklet will not make you an expert however, it does assume a degree of competence in general shiphandling and is therefore intended to supplement this knowledge in understanding what the Master is doing when ...
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Height modernization using fitted geoid models and myrtknet
... 4 Depending on the accuracy requirements, GPS surveys and current high-resolution geoid models can be used, instead of the classical levelling methods. Rene Forsberg from Geodynamics Department, Danish National ...
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