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Showing 1 to 8 of 8 for “"Interval Coverage"”.
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Prediction interval modeling using Gaussian process quantile regression
… thesis a methodology to construct prediction intervals for a generic black-box point forecast model is presented. The prediction intervals are learned from the forecasts of the black-box model and the actual realizations of the forecasted variable by using quantile regression on the observed …
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Examination and Comparison of the Performance of Common Non-Parametric and Robust Regression Models
… The models were evaluated based on confidence interval coverage of regression coefficients, as well as bias and confidence interval width.</p> <p>Finally, results were summarized, conclusions drawn, and suggestions for future applications of the results have been provided.</p>
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Advances in Survival Analysis: Accurate Partial Likelihood Computation by Poisson-Binomial Distributions and Nonparametric Competing Risk Cox Model
… mean squared error while improving confidence interval coverage rates, particularly when ties are frequent or risk score variability is high. The second project develops a nonparametric regression model for competing risks survival data by combining the proportional cause-specific hazards …
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Using the Fraction of Missing Information (FMI) in Selecting Auxiliary Variables to Impute Missingness in Confirmatory Factor Analysis (CFA)
… bias, mean squared error (MSE), and confidence interval coverage of parameters. In addition, the difference between the inclusive and restrictive strategies was examined using empirical data where missing data were designed with two levels of missingness (15% and 30%) and two missingness …
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The Impact of Sample Size, Prevalence, Estimation Method and Other Factors When Estimating Multilevel Logistic Models
… mean estimates of statistical power, confidence interval coverage and width, and likelihood of non-positive definite G-matrices, other key features of multilevel models including the level of random intercept and slope variance and estimation method also impact results. Greater levels of …
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Some applications of minimum norm quadratic estimation and eigenvalue-based test for heteroskedasticity
… is investigated through simulated confidence interval coverage probabilities of the regression coefficients. Although MINQUE generally has the largest MSE, it performs relatively well in terms of the coverage probabilities. We also apply MINQUE for a class of autoregressive conditional …
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Model-Based Measures of Interrater Agreement
… approach can perform well in terms of confidence interval coverage when the number of items/raters is on the order of 60 or more. For the robustness of the new estimation method, the bootstrap approach can perform well under the assumption that both random effects follow a t distribution with …