total least-squares estimation
Model estimation of cerebral hemodynamics between blood flow and volume changes: a data-based modelling approach
... classical least squares algorithms and the standard statistical analysis for these algorithms require certain assumptions: the ‘input’ (independent) variables say φ k (n ) in (5) are measured without ...
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The element wise weighted total least squares problem
... parameter estimation problem is typically defined as an optimization problem: an appropriate cost function depending on the data is minimized over the estimated param- ...the least-squares (LS) ...
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On the equivalence between Total Least Squares and Maximum Likelihood PCA
... parameter estimation, it can be used for prediction provided the solu- tion is appropriately computed ...(at least in the example investigated) minimal predic- tion ...
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AIC under the framework of least squares estimation
... In the original formulation of AIC, it is assumed that the sample size is sufficiently large; thus, if the sample size is not large enough relative to the number of parameters which must be estimated, the AIC may perform ...
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Review of rational (total) nonlinear dynamic system modelling, identification, and control
... The first step in the above computation is to initialise the parameters. A sensible choice will provide tremendous help for the resultant parameter estimation. A wrong choice of the initial parameters can lead to ...
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High performance numerical algorithms and software for structured total least squares
... In Section 2, we define formally the class of problems solved by the package and describe the solution method used. Section 3 outlines the proposed algorithm. The implementation details necessary to use the software ...
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Block Toeplitz/Hankel structured total least squares
... is the parameter of interest, proved to be a useful parameter estimation technique. It became especially popular since the early eighties due to the development [8] of reliable solution methods based on singular ...
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Least squares estimation for GARCH (1,1) model with heavy tailed errors
... In this section we present the results of an application of the proposed es- timator to two time series of financial returns. First, we consider a time series of daily (percentage) log-returns on the S&P 500 index ...
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Adaptive matching pursuit with constrained total least squares
... model the grid as an unknown parameter, and adaptively search for the best one. We choose harmonic retrieval to demonstrate the performance of AMP-CTLS. The algo- rithm can also be applied to jointly estimate range and ...
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Total Least Squares Fitting the Three-Parameter Inverse Weibull Density
... parameter estimation is the least squares ...ordinary least squares (OLS) fitting problem for the three-parameter inverse Weibull density is considered by Maruši´c et ...weighted ...
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ESTIMATION ACCURACY OF EXPONENTIAL DISTRIBUTION PARAMETERS
... with estimation of parameters of the two parameter (location and scale) exponential ...the least squares method (LSM), relative least squares method (RELS), ridge regression method ...
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Deformation analysis with Total Least Squares
... classical least squares and this ignorance remains as an uncertainty in the solution ...parameter estimation in lin- ear models that include error in -some or all- variables ...
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Overview of total least squares methods
... structured total least squares ...the total least squares approach for spectral estimation with extensions to decimation and multichannel data quantification [35, ...the ...
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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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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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Application of structured total least squares for system identification and model reduction
... structured total least squares method for MIMO system identifi- cation, which is the main contribution of the paper, is ...structured total least squares method for system ...
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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
... Overall, the results strongly suggest that there is an inverse relationship between economic activity and road trauma. The negative sign of the unemployment rate coefficient in road safety models has been well discussed ...
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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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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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Application of structured total least squares for system identification and model reduction
... The Total Least Squares Problem: Computational Aspects and Analysis (Philadelphia, PA: SIAM, 1991), and more than 130 papers in international journals and 140 conference ...
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