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weighted least square error estimator

On the Equivalence of the Weighted Least Squares and the Generalised Least Squares Estimators, with Applications to Kernel Smoothing

On the Equivalence of the Weighted Least Squares and the Generalised Least Squares Estimators, with Applications to Kernel Smoothing

... generalised least squares estima- tor of the regression parameters is equivalent to the weighted least squares ...measurement error, where optimality has to be intended in the Gauss-Markov ...

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Empirical likelihood based inference in Poisson autoregressive model with conditional moment restrictions

Empirical likelihood based inference in Poisson autoregressive model with conditional moment restrictions

... likelihood estimator, the least squares estimator and the weighted least squares estimator, which do not utilize the conditional moment ...mean square errors, a comparison ...

13

Asymptotic Properties of the Weighted Least Squares Estimator Under Moments Restriction

Asymptotic Properties of the Weighted Least Squares Estimator Under Moments Restriction

... Although we focus in this report on Theorem 1, the paper gives also extensions of the model by relaxing two assumptions. Theorem 2 gives the large sample results for the case where population from which the sample was ...

14

Least Orthogonal Distance Estimator and Total Least Square

Least Orthogonal Distance Estimator and Total Least Square

... Least Orthogonal Distance Estimator and Total Least Square Naccarato, Alessia and Zurlo, Davide and Pieraccini, Luciano Department of Economics - Roma Tre University.[r] ...

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COMPARISON OF LEAST MEDIAN SQUARE AND ORDINARY LEAST SQUARE METHODS IN THE PRESENCE OF OUTLIERS

COMPARISON OF LEAST MEDIAN SQUARE AND ORDINARY LEAST SQUARE METHODS IN THE PRESENCE OF OUTLIERS

... Median Square) have uniformly higher residual and standard errors than those from the regression estimates of the ordinary least ...ordinary least squares provides optimum estimates when the data set ...

10

Noise Cancellation in Stochastic Wireless Channels using Coding and Adaptive Filtering

Noise Cancellation in Stochastic Wireless Channels using Coding and Adaptive Filtering

... the error signal with respect the tap weight ...Normalized Least Mean Square Algorithm (NLMS), which is a variant of the LMS algorithm, by normalizing with the power of the ...

5

Statistical Study of Least Mean Square and Normalised Least Mean Square Algorithms

Statistical Study of Least Mean Square and Normalised Least Mean Square Algorithms

... the Least Mean Square(LMS)and the Normalized Least Mean Square(NLMS) algorithms with particular cyclostationary input signals and an unknown system in a system identifica- tion ...

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Performance of Weighted Least Square Filter Based Pan Sharpening using Fuzzy Logic

Performance of Weighted Least Square Filter Based Pan Sharpening using Fuzzy Logic

... The actual evaluations on the complete functionality around the merged perception from the encouraged place in addition to that regarding your wavelet place in addition to 4 recently-pro[r] ...

6

Improved Weighted Least Square Filter Based Pan Sharpening using Fuzzy Logic

Improved Weighted Least Square Filter Based Pan Sharpening using Fuzzy Logic

... Kumar, "Image fusion of the multi-sensor lunar image data using wavelet combined transformation." In Recent Trends in Information Technology ICRTIT, 2011 International Conference on, pp.[r] ...

6

An Efficient Algorithm to Design Nearly Perfect-Reconstruction Two-Channel Quadrature Mirror Filter Banks

An Efficient Algorithm to Design Nearly Perfect-Reconstruction Two-Channel Quadrature Mirror Filter Banks

... The error measure to be minimized is formulated as a weighted sum of pass-band error and stop-band residual energy of low-pass prototype filter and the square error of the distortion ...

7

Standard and proportional error model comparison for logistic growth of green algae (Raphidocelis subcapiala)

Standard and proportional error model comparison for logistic growth of green algae (Raphidocelis subcapiala)

... proportional error term in the statistical model. Error is always a confounding variable in in vivo exper- iments that must be accounted for to obtain reliable uncertainty ...of error in the ...

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Two stage weighted least squares estimator of the conditional mean of observation driven time series models

Two stage weighted least squares estimator of the conditional mean of observation driven time series models

... The rest of the paper is organized as follow. Section 2 provides general regularity con- ditions for CAN of the WLS estimators and compares these estimators with the MLE and QMLEs. In Section 3, more explicit CAN ...

44

An Error Controlled Method to Determine the Stellar Density Function in a Region  of the Sky

An Error Controlled Method to Determine the Stellar Density Function in a Region of the Sky

... C = C  σ ≤ σ σ σ σ σ ≤ µ (45) where Tol and µ small numbers. In writing Equation (45) we do not mean to establish this particular defini- tion of an acceptable solution set, as it is only intended to give the users of ...

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Corrigendum: Spectral thresholding quantum tomography for low rank states (2015 New J  Phys  17 113050)

Corrigendum: Spectral thresholding quantum tomography for low rank states (2015 New J Phys 17 113050)

... In this corrigendum to the paper Butucea et al ( 2015 New J. Phys. 17 113050 ) we point out an error in one of the theoretical results describing the upper bound to the operator norm error of the ...

5

IJCSMC, Vol. 5, Issue. 7, July 2016, pg.467 – 471 A Study on Exploration of Service Discovery in Adhoc Network

IJCSMC, Vol. 5, Issue. 7, July 2016, pg.467 – 471 A Study on Exploration of Service Discovery in Adhoc Network

... the error reduction over the ...the error correction with balancing over the ...The error rate analysis at different level is provided to achieve the effective Distribution over the ...

5

Modification of Ratio Estimator for Population Mean

Modification of Ratio Estimator for Population Mean

... proposed estimator works better than the other existing estimators having the minimum Mean Square Error (MSE) and the highest Percentage Relative Error ...

5

An Improved Estimator Of Finite Population Mean Using Auxiliary Attribute(S) In Stratified Random Sampling Under Non-Response

An Improved Estimator Of Finite Population Mean Using Auxiliary Attribute(S) In Stratified Random Sampling Under Non-Response

... In the present study, we propose a new estimator for population mean using Singh et al. (2007) and Malik and Singh (2013) estimators in the case of stratified random sampling when the information is available in ...

9

Performance and Analysis of Channel Estimation Techniques for LTE Downlink System under Fading with Mobility

Performance and Analysis of Channel Estimation Techniques for LTE Downlink System under Fading with Mobility

... In [2] channel estimation for LTE downlink based on the interpolation to estimate channel coefficients. Lagrange polynomial interpolation method is proposed. Here, they perform the estimation for downlink LTE system for ...

13

Error analysis for \(l^{q}\) coefficient regularized moving least square regression

Error analysis for \(l^{q}\) coefficient regularized moving least square regression

... upper error bound of the algorithm ...the error quantity into the approximation error, the hypothesis error and the sample error and obtained their upper bounds using error ...

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Estimators of Linear Regression Model and Prediction under Some Assumptions Violation

Estimators of Linear Regression Model and Prediction under Some Assumptions Violation

... Iyaniwura and Nwabueze [27], Nwabueze [28-30], Ay- inde and Ipinyomi [31] and many other authors have not only examined these estimators but have also noted that their performances and efficiency depend on the structure ...

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