sequential least squares estimation
Asymptotic properties of least squares estimation for a new fuzzy autoregressive model
... The time series forecasting investigates the relations on the sequential set of past data measured over time to forecast the future values. The area has been widely studied, and traditional forecasting is ...
10
Ordinary Least Squares Estimation of a Dynamic Game Model
... The estimation of dynamic games is known to be a numerically challenging ...asymptotic least squares estimators to Pesendorfer and Schmidt-Dengler’s (2008), which includes several well known ...
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Communication efficient distributed weighted non linear least squares estimation
... Sequential distributed recursive schemes conforming to the consensus + innovations (see for example, [19] and Eq. (16) ahead) type update, where the agents’ knowledge of the model is limited to themselves have ...
15
05_Linear_Regression_1.pdf
... Outlines Overview Introduction Linear Algebra Probability Linear Regression 1 Linear Regression 2 Linear Classification 1 Linear Classification 2 Kernel Methods Sparse Kernel Methods Neural Networks 1 Neural Networks 2 ...
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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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Robust Regression Analysis with LR Type Fuzzy Input Variables and Fuzzy Output Variable
... Weighted Least Squares estimation ...the Least Me- dian Squares-Weighted Least Squares (LMS-WLS) estimation procedure, we give robust estimation steps for ...
17
Burr type III Software Reliability Growth Model with Interval Domain Data
... One of the most difficult problems of software industry is to ship a reliable product. Therefore it is necessary to have accurate and fast estimation techniques for verifying software reliability. Software ...
7
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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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 ...
7
Estimation and Inference in Unstable Nonlinear Least Squares Models (Final)
... a sequential procedure for selecting the number of break points in the sample based on various F-statistics for parameter ...stage least squares models by Hall, Han, and Boldea ...of ...
164
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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Least squares estimation for GARCH (1,1) model with heavy tailed errors
... In this paper, we suggest using LSE for the estimation of a GARCH (1,1) model. The estimator is based on the log transformation of the squared data. We establish the consistency and asymptotic normality of the ...
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Implementation of the Least-Squares Lattice with Order and Forgetting Factor Estimation for FPGA
... The most important property making the RLS lattice suitable for the hypotheses estimation is its modular struc- ture. The RLS lattice filter consists of a cascade of identical modules. Each module implements the ...
11
On the Equivalence of the Weighted Least Squares and the Generalised Least Squares Estimators, with Applications to Kernel Smoothing
... The paper establishes the conditions under which the generalised least squares estima- tor of the regression parameters is equivalent to the weighted least squares estimator. The equivalence ...
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Estimation of a system of national accounts: implementation with mathematica
... The reader is referred to Danilov and Magnus (2008) for a detailed description of the estimation problems stated below. Although they are equivalent and all yield the same estimations, the performance of their ...
16
Asymptotic properties of weighted least squares estimation in weak parma models
... weighted least squares estimators for invertible and causal PARMA models with dependent but uncorrelated ...of estimation and inference in PARMA models under the assumption of independent errors can ...
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Using Least Squares Support Vector Machines for Frequency Estimation
... frequency estimation with following attractive features: The estimator can work efficiently without the need of statistics knowledge of the observa- tions, and the estimation performance is insensitive to ...
5
ON RECURSIVE PARAMETRIC IDENTIFICATION OF WIENER SYSTEMS
... parametric estimation problem by a simple input-output data reordering and by a following data ...on sequential reconstruction of the values of intermediate signal by following use of the ordinary recursive ...
8
A Least-squares Approach to Direct Importance Estimation
... LSIF is shown to be efficient in computation, but it tends to share a common weakness of reg- ularization path tracking algorithms, that is, accumulation of numerical errors (Scheinberg, 2006). The numerical problem ...
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Estimation and inference in unstable nonlinear least squares models
... Our estimation procedure is similar to that of Bai and Perron (1998), but the proofs are different since they require empirical process theory results developed in this paper, results that may be useful in other ...
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