[PDF] Top 20 Generalized and pseudo-generalized trimmed means for the linear regression with AR(l) error model
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Generalized and pseudo-generalized trimmed means for the linear regression with AR(l) error model
... introduce the concepts of GTM and PGTM in Section 2 and establish their large sample theory in Section ...Finally, the proofs of the theorems are displayed in ...2. Generalized ... See full document
9
Linear trimmed means for the linear regression with AR(1) errors model
... is the class of ð a 1 , a 2 Þ linear trimmed mean’s? However, we do not study the scope of the linear trimmed ...In the literature, consideration has been given to ... See full document
11
Trimmed least squares estimator as best trimmed linear conditional estimator for linear regression model
... DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our ...agents, and our ... See full document
16
Parametric simultaneous robust inferences for regression coefficient under generalized linear models
... On the other hand, it is noted that when the simulated data sets are generated under the alternative hypothesis H A , the adjusted Wald and score statistics not only rightly reject ... See full document
20
Symmetric regression quantile and its application to robust estimation for the nonlinear regression model
... indices for identifying outliers. We propose a class of symmetric quantiles for estimating unknown nonlinear regression conditional ...than regression quantiles considered by Koenker ... See full document
18
A multivariate parallelogram and its application to multivariate trimmed means
... (b) The two trimmed means have nearly the same ...When the correlation coefficient ρ gets larger, the asymptotic generalized variances of the two trimmed ... See full document
10
Then multiple linear regression model will be discussed
... uses the statistical techniques to analyze the real data. With this knowledge, we not only develop the ability to interpret the econo- metric models but also make inference and ... See full document
2
Extensional Completed L-measure and Its Choquet Integral Regression Model
... Abstract: The well known fuzzy measures, X-measure and P-measure, have only one formulaic ...measure with infinitely many solutions based on P- measure was proposed by our previous work, called ... See full document
2
Robust diagnostics for the negative binomial regression model
... analysis for locally stationary time series Speaker: Marc Hallin, Universite Libre de Bruxelles, Belgium Stefan Birr, Holger Dette, Stanislav Volgushev Classical spectral methods are subject to two fundamental ... See full document
112
Modeling crash frequency and severity using multinomial-generalized Poisson model with error components
... Null model: with three constants for crash severity (market share) and a single constant for generalized Poisson ...severity. The cause and effect relationship may ... See full document
10
Generalized confidence intervals for the ratio of means of two normal populations
... exact generalized approaches based on generalized p-values and generalized con&dence intervals to solve the well-known Fieller-Creasy problem, which is widely used in many important ... See full document
12
Error Analysis of The Generalized MAC Scheme
... OF THE GENERALIZED MAC SCHEME YIN-LIANG HUANG ∗ , JIAN-GUO LIU † , AND WEI-CHENG WANG ‡ ...analysis for the generalized MAC (gMAC) scheme on curvilinear domains proposed earlier ... See full document
38
Estimation and prediction of generalized growth curve with grouping variances in AR(q) dependence structure
... outside the unit circle kxk ¼ 1 in the complex plane and s l > 0 for l ¼ 1; ...In the grouping of the variances, we assume that there are g i members in the ... See full document
17
On power and sample size calculations for likelihood ratio tests in generalized linear models
... KEY WORDS: Generalized linear models; Likelihood ratio test; Logistic regression; Noncentral chi-square; Poisson regression; Sample size; Score test; Statistical power.. Intro[r] ... See full document
5
A Generalized Shape-Axis Model for Planar Shapes
... a generalized shape-axis (SA) model for representing both open and closed planar ...curves. The SA model is an effective way to represent shapes by compar- ing their ...clockwise ... See full document
5
An Application of the Generalized Shrunken Least Squares Estimator on Principal Component Regression
... At the point in which the analyst has determined, by the use of the diagnostics, that Multicollinearity is a problem, often a substantial benefit may be derived from an attempt to eliminate ... See full document
38
Approximate Proximal Algorithms for Generalized Variational Inequalities with Paramonotonicity and Pseudomonotonicity
... algorithm for solving generalized variational inequalities in Hilbert ...under the paramonotonicity and pseudomonotonicity assumptions of the ... See full document
8
A generalized methodology for low-error and area-time efficient fixed-width Booth multipliers
... 51 have been widely studied. King and Swartzlander [3] analyzed an adaptive error-compensation bias and proposed an n-bit fixed- width multiplier. In [ l , 21, we generalized[r] ... See full document
4
ADDING A VARIABLE IN GENERALIZED LINEAR-MODELS
... Association and American Society for Quality Stable URL: ...of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at ... See full document
5
Generalized synchronization of chaotic systems by pure error dynamics and elaborate Lyapunov function
... t The generalized synchronization is studied by applying pure error dynamics and elaborate Lyapunov function in this ...paper. Generalized synchronization can be obtained by pure ... See full document
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