Generalized Least Squares Estimation
Generalized Least Squares Estimation for Cointegration Parameters Under Conditional Heteroskedasticity
... Despite the superconsistency of standard estimators for the cointegration parameters in a VAR model, the small sample properties are often poor. This state of affairs is particularly problematic because the cointegration ...
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The Relative Efficiency of the Conditional Root Square Estimation of Parameter in Inhomogeneous Equality Restricted Linear Model
... the generalized conditional root square estimation and the spe- cific conditional root square estimation in paper [1,2] in inhomogeneous equality restricted linear ...the generalized ...
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Asymptotic properties of weighted least squares estimation in weak parma models
... of least squares estimation for invertible and causal weak PARMA ...ordinary least squares (OLS), weighted least squares (WLS) for an arbitrary vector of weights, ...
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Least squares estimation of hydraulic conductivity from field data
... Y. Saad and M. H. Schultz, 1986. \ GM- RES : A Generalized Minimal Residual Al- gorithm for Solving Nonsymmetric Linear Systems", SIAM Journal on Scientic and Statistical Computing, 7 (3), pp. 856{869. F. ...
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Least squares estimation for GARCH (1,1) model with heavy tailed errors
... their squares, a notable example being the daily financial ...the generalized autoregressive conditionally heteroskedasticity (GARCH) model, suggested by Bollerslev (1986), and its numerous ...
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AIC under the framework of least squares estimation
... In this note we explain the use of the Akiake Information Criterion and its related model compar- ison indices (usually derived for maximum likelihood estimator inverse problem formulations) for use with least ...
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The Equivalence of the Maximum Likelihood and a Modified Least Squares for a Case of Generalized Linear Model
... the generalized estimating equations whose solution is an estimate of the fixed effects; consequently we do neither insist on the random effects nor on the parameter generating the variance-covariance matrix of ...
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Burr type III Software Reliability Growth Model with Interval Domain Data
... Parameter estimation is given primary importance for software reliability ...Parameter estimation can be achieved by applying a technique of MLE which is the most important and widely used estimation ...
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The search for a robust measure of road safety advertising effectiveness : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Marketing at Massey University, Palmerston North
... The models of the New Zealand campaign have varied in terms of, levels of data monthly, quarterly a nd yearly, estimation ordinary least squares, autoregression generalised least squares[r] ...
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An inverse problem formulation methodology for stochastic models
... If the error distribution is unknown and we suspect that relative error is present in the measurement, then the assumption of constant variance of the error in the longitudinal data does not hold. In such cases, a ...
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Least squares estimation of probability measures in the Prohorov metric framework
... this estimation problem, one encounters a rich body of mathematical ...the estimation problem which has been developed and tested computationally over the past several decades [4, 8, 16, 21] (Section ...the ...
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Empirical distributions in least squares estimation for distributed parameter systems
... Our goal in this work is to derive a number of asymptotic results for a sequence of empirical or sample distributions for measurement errors in a least squares framework. The impact of such a study is that ...
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Estimation and Inference in Unstable Nonlinear Least Squares Models (Final)
... ever, it is plausible that, under the alternative, parameters follow a certain predefined process, such as a random walk. Nyblom and M¨akel¨ainen (1983) derive locally most powerful sup F-tests against this alternative. ...
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Title: Multicarrier Iterative Generalized Least Squares Data Extraction in Digital Images
... iterative generalized least squares (IGLS) procedure was developed to blindly recover unknown messages hidden in image hosts via SS ...iterative generalized least squares ...
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Robust Regression Analysis with LR Type Fuzzy Input Variables and Fuzzy Output Variable
... suggested generalized fuzzy weighted least squares method for an outlier condition, making weighted with degree of membership and lean on an interaction with the ...the least squares of ...
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Asymptotic properties of least squares estimation for a new fuzzy autoregressive model
... In particular, Ozawa [] proposed a fuzzy auto-regressive (AR) model to forecast the data of living expenditure of workers’ household in Japan, where the identification and the estimation of its model and the ...
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Implementation of the Least-Squares Lattice with Order and Forgetting Factor Estimation for FPGA
... the estimation of an unknown order and forgetting factor of identified system was developed and implemented as a PCORE coprocessor for Xilinx ...factor estimation was implemented using the logarithmic ...
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Robust estimation of the vector autoregressive model by a trimmed least squares procedure.
... In this paper we propose a robust procedure to estimate vector autoregressive models, to select their order, and to construct confidence bounds around the impulse [r] ...
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Estimation of a system of national accounts: implementation with mathematica
... Bayesian estimation, restricted and unrestricted least-squares estimation and best linear unbiased esti- ...the estimation of unrealized or unavailable national accounts data and for ...
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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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