Least Squares Estimation
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Least squares estimation of probability measures in the Prohorov metric framework
... general least squares ...likelihood estimation (also in a frequentist framework) can be established with little difficulty from the results presented ...the estimation of the unknown ...
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Asymptotic properties of least squares estimation for a new fuzzy autoregressive model
... numbers. Least squares estimation is derived, and the asymptotic distribution of the proposed estimator is ...This estimation procedure is well defined because if we use crisp data instead of ...
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Empirical distributions in least squares estimation for distributed parameter systems
... We have concentrated on the convergence and the rate of convergence of empirical processes of residuals from nonlinear least squares estimation problems. These processes can be used to answer many ...
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ORIGIN DESTINATION DISAGGREGATION USING FRATAR BIPROPORTIONAL LEAST SQUARES ESTIMATION FOR TRUCK FORECASTING
... nonlinear least-squares estimation to obtain row and column factors for splitting trip totals from and to larger geographical areas into smaller ...
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Asymptotic properties of weighted least squares estimation in weak parma models
... In recent years, a large part of the time series and econometric literature was devoted to weaken the strong noise assumption. In particular, Romano and Thombs (1996) showed that the significance limits of the sample ...
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Nonlinear Least Squares Estimation of the Shifted Gompertz Distribution
... parameter estimation in the Bass model by nonlinear least squares fitting the adoption ...weighted least squares estimation of a three-parameter Weibull density with a ...
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AIC under the framework of least squares estimation
... parameter estimation in the framework of a least squares estimation problem ([10] and all the references ...the least squares ...appropriate estimation technique varies; ...
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Communication efficient distributed weighted non linear least squares estimation
... tributed estimation problems of type ...state estimation in power sys- tems; therein, a phasorial representation of voltages and currents is usually utilized, wherein non-linearity in gen- eral emerges from ...
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Least squares estimation for GARCH (1,1) model with heavy tailed errors
... GARCH (1,1) models are widely used for modelling processes with time varying volatility. These include financial time series, which can be particularly heavy tailed. In this paper, we propose a log- transform-based ...
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Generalized Least Squares Estimation for Cointegration Parameters Under Conditional Heteroskedasticity
... All three GLS estimators are typically rather close together in terms of RMSE and MAE. GLS2 and GLS3 results are in fact almost indistinguishable in the figures for all DGPs and sample sizes. Thus, reestimating α in Step ...
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Least squares estimation of joint production functions by the Differential Evolution method of global optimization
... approached estimation of joint production function through ...and estimation of a general implicit production ...of estimation of multiple/joint production functions as an exercise in ...
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Least squares estimation of hydraulic conductivity from field data
... simple nite dierence scheme, containing ux balance conditions over conductivity discontinu- ities, is used to approximate the ow equation. Piecewise constant functions are used for the conductivities, and piecewise ...
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Particle swarm optimization and least squares estimation of NARMAX
... parameter estimation step is performed using various types LLS estimation algorithms because of the excellent characteristics where it is stable and efficient in terms of numerical computation ...
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Least squares estimation of a shift in linear processes
... In the previous subsection, the shift is ignored and the order determination is based on a misspecified model which leads to over estimation. Thus if a high order is identified in practice, one should consider a ...
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Least squares estimation for the subcritical Heston model based on continuous time observations
... have already proved the strong consistency and asymptotic normality of the LSE of (a, b) based on continuous time observations (Yt) t ∈[0 ,T ] , T > 0, in case of a subcritical CIR pr[r] ...
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Ordinary Least Squares Estimation of a Dynamic Game Model
... the estimation problem for a class of dynamic games of incomplete information that generalizes the single agent discrete Markov decision models surveyed in Rust (1994); for a recent survey see Aguirregabiria and ...
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Estimation of groundwater flow parameters using least squares
... is estimation of the subsurface physical pa- rameters, particularly the hydraulic ...a least squares estimation procedure for determining groundwater velocities from limited ...
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Derivative Estimation Based on Difference Sequence via Locally Weighted Least Squares Regression
... In this paper we propose a new methodology to estimate derivatives in nonparametric re- gression. The method includes two main steps: construct a sequence of symmetric difference quotients, and estimate the derivative ...
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On the generalization of linear least mean squares estimation to quantum systems with non-commutative outputs
... optimal estimation of a linear quan- tum system variables given the non-commutative outputs within the framework of non- commutative probability ...a least squares error ...
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The Dual of the Least Squares Method
... the least-squares me- thod (for linear systems) which results as a consequence of the analysis that the mean observational error will fall within certain given ...the least-squares ...
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