• No results found

weighted least-squares estimation

Asymptotic properties of weighted least squares estimation in weak parma models

Asymptotic properties of weighted least squares estimation in weak parma models

... parameter estimation and diagnostic ...on estimation of PARMA models. Pagano (1978) dealt with moment estimation of periodic autoregressive (PAR) ...moment estimation of low order PARMA ...

44

Analysis and interpretation of forest fertilizer experiments

Analysis and interpretation of forest fertilizer experiments

... FURTHER ASPECTS OF ANALYSIS OF FERTILIZER EXPERIMENTS ASSUMPTIONS IN ANALYSIS OF VARIANCE Introduction Underlying assumptions WEIGHTED LEAST-SQUARES ESTIMATION Weighted least-squ'ares es[r] ...

304

Robust Regression Analysis with LR Type Fuzzy Input Variables and Fuzzy Output Variable

Robust Regression Analysis with LR Type Fuzzy Input Variables and Fuzzy Output Variable

... the Weighted Least Squares estimation ...the Least Me- dian Squares-Weighted Least Squares (LMS-WLS) estimation procedure, we give robust ...

17

Nonlinear Least Squares Estimation of the Shifted Gompertz Distribution

Nonlinear Least Squares Estimation of the Shifted Gompertz Distribution

... parameter estimation in the Bass model by nonlinear least squares fitting the adoption ...Nonlinear weighted least squares estimation of a three-parameter Weibull density ...

10

New approaches in estimating linear regression model parameters in the presence of multicollinearity and outliers

New approaches in estimating linear regression model parameters in the presence of multicollinearity and outliers

... ordinary least squares (OLS) method has been the most popular technique for estimating parameters of model due to its optimal properties and ease of ...parameter estimation method in the presence of ...

34

Handling multicollinearity and outliers using weighted ridge least trimmed squares

Handling multicollinearity and outliers using weighted ridge least trimmed squares

... the least-squares estimates of the regression ...ordinary least squares (LS) estimation in the existence of a multicollinearity problem ...

14

Derivative Estimation Based on Difference Sequence via Locally Weighted Least Squares Regression

Derivative Estimation Based on Difference Sequence via Locally Weighted Least Squares Regression

... of convergence. Zhou and Wolfe (2000) derived asymptotic bias, variance, and established normality properties. Heckman and Ramsay (2000) considered a penalized version. In the case of LPR, a polynomial obtained by Taylor ...

25

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

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

... ordinary least squares estimator (LS), the weighted least squares estima- tor (WLS), and the maximum likelihood estimation (MLE), we compute the mean square errors based on the ...

13

Simple estimators of the intensity of seasonal occurrence

Simple estimators of the intensity of seasonal occurrence

... the estimation of seasonal intensity assuming Edwards's periodic model, including maximum likelihood estimation (MLE), least squares, weighted least squares, and a new ...

9

AIC under the framework of least squares estimation

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 ...

16

The element wise weighted total least squares problem

The element wise weighted total least squares problem

... parameter estimation in a linear measurement error model AX ≈ B, A = A 0 + ˜ A, B = B 0 + ˜ B, A 0 X 0 = B 0 with row-wise independent and non-identically distributed measurement errors A ˜ , B ˜ ...total ...

29

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

Particle Swarm Optimization and Differentiation Evolution –Based Weighted Least Squares State Estimation

Particle Swarm Optimization and Differentiation Evolution –Based Weighted Least Squares State Estimation

... State estimation is a technique developed to provide an estimate of an unknown system state variable and to quantitatively analyze the estimated state variable before it is used for real time power -now ...

8

An extension of RSS-based model comparison tests for weighted least squares

An extension of RSS-based model comparison tests for weighted least squares

... likelihood estimation, least squares estimation generally requires only the first two statistical moments of the observations to be specified [13, ...likelihood estimation) [17, ...a ...

19

Communication efficient distributed weighted non linear least squares estimation

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 ...

15

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

... the weighted least squares estimator of a local cubic trend at time t using 2h + 1 consecutive ...trend-cycle estimation in economic time ...trend estimation in the X-12-ARIMA ...

23

Estimation of groundwater flow parameters using least squares

Estimation of groundwater flow parameters using least squares

... Our approach to estimating the hydraulic parameters of an aquifer is to apply least squares. Our data consists of two types of measurements. The rst is pointwise measurements of hydraulic head. These are ...

15

Estimation and inference in unstable nonlinear least squares models

Estimation and inference in unstable nonlinear least squares models

... example, early work by Quandt (1960) suggests using a supremum (sup) type test for inference on a single unknown break-point. Whether in linear or nonlinear set- tings, most subsequent work - see inter alia Anderson and ...

56

Particle swarm optimization and least squares estimation of NARMAX

Particle swarm optimization and least squares estimation of NARMAX

... In this work, we choose the three establish method of LS to compare with another popular technique which is PSO. The PSO have been chosen as a method to compare because of it is stochastic optimization technique in ...

7

Ordinary Least Squares Estimation of a Dynamic Game Model

Ordinary Least Squares Estimation of a Dynamic Game Model

... We have shown there can be some non-trivial computational gains in de…ning estimators that opti- mize objective functions constructed in terms of expected payo¤s instead of choice probabilities for the estimation ...

33

Show all 10000 documents...

Related subjects