[PDF] Top 20 Symmetric regression quantile and its application to robust estimation for the nonlinear regression model
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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 ...samples, symmetric quantiles are more ... See full document
18
A Quantile Regression Approach to the Multiple Period Value at Risk Estimation
... According to Proposition 4 in Kamien and Tauman (1986), in an oligopoly, when the number of firms is small (or very large), the strategy of entering the market and simultaneously ... See full document
26
Robust diagnostics for the negative binomial regression model
... bootstrap and adjusting for time effects Presenter: Eun Ryung Lee, Sungkyunkwan University, Korea, South A central task in comparative politics is to locate party positions in a certain political ... See full document
112
Generalized and pseudo-generalized trimmed means for the linear regression with AR(l) error model
... After the development of the GTM, the next interesting problem is whether when the parameter is unknown, the trimmed mean of ...have the same asymptotic behavior as displayed by ... See full document
9
Robust cerebellar model articulation controller design for unknown nonlinear systems
... theory and traditional feedback ...of the controlled system dynamics and its environment; the objection for the real-time application is unrealizable for ... See full document
5
Regression modeling for nonparametric estimation of distribution and quantile functions
... University and Georgia Institute of Technology Abstract: We propose a local linear estimator of a smooth distribution ...techniques to observations from a regression model in which the ... See full document
18
Corporate Governance and Cash Holdings: A Quantile Regression Approach
... holding the CEO position affects cash holdings negatively in high cash holding ...Methodology and data description ...governance to the cash policy in firms with different levels of cash ... See full document
12
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 ...of the lambda-measure and P-measure. For evaluating the Choquet integral ... See full document
2
A new concept for adding adjustment to the fitting process on regression model
... With the progress of information technology, RFID has various applications such as in scanning volume materials at one ...time. For above reason, the subject of this thesis is using RFID along with ... See full document
1
Asymmetric inflation dynamics: Evidence from quantile regression analysis
... that the inflation rates in 12 OECD countries are globally meaning-reverting based on the quantile inference, in sharp contrast to the counterparts from the univariate unit root ... See full document
6
A statistical regression model for estimation of acrylamide concentrations in French fries for excess lifetime cancer risk assessment
... survey for adolescents in Taichung This study was approved by the Ethics Review Board at China Medical University College of Public Health, Taichung, ...order to obtain the French fries intake ... See full document
6
A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and
... of the EM algorithm. The first occurs when the data indeed has missing values, due to problems with or limitations of the observation ...process. The second occurs when ... See full document
15
A nonparametric regression model for virtual humans generation
... interpolation and shape deformation may be able to produce good quality results for body movements and novel views ...16e and 17 provide the comparisons with the view ... See full document
25
Logistic regression model for predicting the failure probability of a landslide dam
... flow and result in landslide dams; they occur in many regions of the ...world. The formation and disappearance of natural lakes involve a complex earth –surface ...According to ... See full document
10
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
Clustering and Symbolic Regression for Power Consumption Estimation on Smartphone Hardware Subsystems,"
... Clustering and Symbolic Regres- sion (CSR) power estimation method for smartphone sub- ...improves the accuracy of subsystem power estimation by investigating nonlinear ... See full document
12
Toward the Best Feature Model for Network Intrusion Detection Using Stepwise Regression and Support Vector Machine
... of the binary SVM classification ...one-against-all and one-against-one methods. The one-against-all method is easy for ...is the number of classes. The p-th SVM is trained by ... See full document
6
Conditional variance estimation in heteroscedastic regression models
... Abstract The differences of thermal properties between rigid rod and flexible bisphenol A (DGEBA) epoxies were studied using modulated differential scanning calorimeter (MDSC), thermal gravimetric analyzer ... See full document
4
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 the ... See full document
11
Applying Particle Swarm Optimization to Parameter Estimation of the Nonlinear Muskingum Model
... Kennedy and Eberhart 共1995兲, inspired by social behavior of bird flocking or fish schooling 共Clerc and Kennedy ...In the past several years, PSO has been successfully applied including hydrological ... See full document
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