Regression Results and Robustness
Consistency and robustness of kernel based regression
... Our results concerning the influence function of kernel based regression (Theorem 18 and Corollary 19) are valid under the assumption that the loss function is twice continuously differentiable, whereas our ...
29
Robustness of bootstrap in instrumental variable regression
... IV regression technique particularly in its finite sample performance, and that approxima- tions based on the asymptotic theory may yield poor results (see, ...IV regression estimators and related ...
38
Robustness of bootstrap in instrumental variable regression
... IV regression technique particularly in its finite sample performance, and that approxima- tions based on the asymptotic theory may yield poor results (see, ...IV regression estimators and related ...
41
Robustness Procedures in Economic Growth Regression Models
... For all models, the population variable, proportion of young dependents, has a negative and significant effect on income growth. The estimated coefficient of -0.09 (for model 1) implies that a one-percentage point ...
13
Investigation into the robustness of Evolutionary Programming Regression for sedimentation study
... Polynomial Regression (EPR) has been used to determine the total sediment load in selected rivers in ...the robustness and generalization ability of EPR modelling, the approach that is generally adopted is ...
7
Robustness of reweighted Least Squares Kernel Based Regression
... the robustness of the methods under ...way robustness is a stronger requirement than ...stable results when adding any possible point, even an extremely unlikely ...between robustness and ...
17
Bouligand Derivatives and Robustness of Support Vector Machines for Regression
... are able to “learn”, but it is also important to investigate the robustness properties for such statistical learning methods. In almost all cases statistical models are only approximations to the true random ...
22
Within- and between-group regression for improving the robustness of causal claims in cross-sectional analysis
... The authors thank the participants of the C8 Health project for their contributions to this study. They also thank Dr Tony Fletcher and Dr Ben Armstrong for their comments on the manuscript and Amy Beierholm and Susan ...
10
Performance and robustness of probabilistic river forecasts computed with quantile regression based on multiple independent variables
... quantile regression (QR) to pre- dict exceedance probabilities of various water levels, includ- ing flood stages, with combinations of deterministic fore- casts, past forecast errors and rates of water level rise ...
22
A simulation study of the robustness of the least median of squares estimator of slope in a regression through the origin model
... Based on 1000 simulations for each combination of parameters and for the 3 mixed distributions, the results are summarized below in tables and plots. The estimates of and the root mean squared errors are ...
48
Correlates of statewise participation in the great Indian growth turnaround: some preliminary robustness results
... nary robustness results In Ghate and Wright (forthcoming), henceforth GW we showed that while the common nature of the growth turnaround, as identi…ed by the V-Factor, appears to correspond fairly well to ...
10
A comparison between Joint Regression Analysis and the Additive Main and Multiplicative Interaction model: the robustness with increasing amounts of missing data
... Another comparison can be made regarding the sums of the sums of squares of residuals for the two procedures and two algorithms (Table 2). Here the advantage of the zigzag and double minimization algorithms over the two ...
8
Assessment of the consistency and robustness of results from a multicenter trial of remission maintenance therapy for acute myeloid leukemia
... Cox regression model with treatment as the covariate of interest (coded 1 = treatment, 0 = control, so that HR>1 indicates treat- ment benefit), and stratification for country and com- plete remission (CR1 vs ...
8
Robustness of Bootstrap in Instrumental Variable Regression
... IV regression which is one of the most popular econometrics models, and studies separately the effects of outliers in dependent variables, endogenous regressors, and ...IV regression should seriously think ...
25
Robustness for regression models with asymmetric error distribution
... the regression models with asymmetrical error distribution, more precisely, with extreme value error ...These regression models are applied in a variety of different application domains, ...
203
Beam results Robustness and Timing Performance
... ● In high luminosity running the system starts to be dominated by the Muon/XTRP arriving time rather than RECES. ● Both RunIIa and RunIIb systems will see the same dominating latency [r] ...
23
Robustness of maximum likelihood estimates for mixed Poisson regression models
... Gustafson (1996) used an influence function approach (Hampel et al., 1986) (Huber, 1981) to examine the robustness of maximum likelihood estimates for certain conjugate mixture models un[r] ...
23
New Results in ell_1 Penalized Regression
... We compare Bayesian trend filtering (BTF), with the priors dexp and gdp, against four different methods: trend filtering (TF) from Tibshirani [2014], Bayesian additive regression trees (BTree) from Chipman et al. ...
91
Evaluating the Robustness of Learning Analytics Results Against Fake Learners
... that the data collected represent genuine learning behavior, and that there are hidden causal relationships between learners behavior and their success, which can be discovered using Educational Data Mining (EDM). Fake ...
14
Understanding the Results of Multiple Linear Regression: Beyond Standardized Regression Coefficients
... of regression metrics within a single ...linear regression to be discussed here, such as dominance analysis (Azen & Budescu, 2003) and relative weights (Gro¨mping, 2006; Tonidandel, LeBreton, & ...
25