WTP - Interval regression model with refusals
First Birth Interval: Cox Regression Model with Time Varying Covariates
... individual. Regression models for time to event data have been based on the Cox regression model, which assumes that the underlying hazard function for any two levels of some covariates is ...
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Socioeconomic and Demographic Determinants of Birth Interval in Bangladesh: A Statistical Analysis Using Survival Mixed Regression Model and Proportional Hazard Regression Model
... birth interval patterns, maternal and childhealth during a woman’s whole reproductive ...birth interval considering relative influencing ...Mixed Regression Model considers the existence of ...
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Linear Regression Analysis for Symbolic Interval Data
... the interval data of the dependent variable and the indepen- dent variables are correlated with each ...the interval lengths of the two variables may not depend on each ...consider model 2 data and ...
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A Midpoint–Radius approach to regression with interval data
... of regression problems highly depends on the nature of input–output data [15] ...the regression problem using Impre- cise-Inputs and Imprecise-Outputs (II–IO) ...fuzzy regression with CI–CO and CI–IO ...
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Tree-based Regression for Interval-valued Data
... no interval structure between ...linear model to allow for additional model ...an interval could result in loss of geometric information and less interpretability ...
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Simultaneous interval regression for K-nearest neighbor
... an interval that must contain a desired proportion of the true unknown distribution that might have generated this sample ...for regression. Simultaneous interval regression, introduced in ...
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A Logistic Regression Mixture Model for Interval Mapping of Genetic Trait Loci Affecting Binary Phenotypes
... log 10 e 2 T ; or 0.217T approximately, where T is given by (7). Note that the distribution of T is convenient to implement for determining a threshold at a prespeci- fied significance level via a Monte Carlo method. The ...
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Proportional Hazard Regression Model Under Partly Interval-Censoring Assumption with Application to Prison Data
... the interval-censored observations from the entire data set, nevertheless, leads to enlarged standard error and estimation bias (Wu et ...correct model to PIC data because of factors such as violat io ns of ...
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On Sharp Identification Regions for Regression Under Interval Data
... 6 An Identification Region Based on a Set-Domained Loss Function Now we try to establish a region, which could be understood as a compromise between SMR and SCR. The idea here is that we look on loss functions that are ...
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Penalized Regression for Interval-Censored Times of Disease Progression
... with interval-censored failure time ...hazards model with a piecewise constant baseline hazard is augmented by including one of several possible penalty ...
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An Interval-Censored Model for Predicting Myopic Regression after Laser In Situ Keratomileusis METHODS. Study Subjects
... ⫻ 共1 ⫺ 3 兲共1 ⫺ 4 兲共1 ⫺ 5 兲] ⫽ 1 ⫺ 关共1 ⫺ 0.6002兲共1 ⫺ 0.2975兲 ⫻ 共1 ⫺ 0.5092兲共1 ⫺ 0.3211兲共1 ⫺ 0.3126兲] ⫽ 0.9357. (Table 3). The eyes with a higher score had a greater proba- bility of myopia regression. The ...
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Model-Robust Interval Estimation
... of interval estimation, length-optimal confidence intervals, which is a general methodology for modifying score and likelihood-type confidence intervals that yields intervals with shorter ...Huber ...
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Finding a Better Confidence Interval for a Single Regression Changepoint Using Different Bootstrap Confidence Interval Procedures
... the regression coefficients and the ...line model and derived the maximum likelihood estimator (MLE) of the changepoint by its marginal likelihood function and presented the asymptotic distribution of the ...
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Interval type 2 A intuitionistic fuzzy logic for regression problems
... • Abalone dataset [63] The effectiveness of the proposed model is demonstrated using a real world high dimensional regression datasets namely the abalone dataset. The abalone dataset is a highly noisy ...
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Research Article Analyzing Big Data with the Hybrid Interval Regression Methods
... the interval regression model with crisp inputs and interval ...both interval inputs-interval output and fuzzy inputs-fuzzy output will be ...
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Semi-parametric regression analysis of interval-censored failure time data
... 3.5 Discussion and Concluding Remarks This chapter discussed regression analysis of current status failure time data arising from the additive hazards model when there exist missing and auxiliary ...
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Proportional subdistribution hazards regression with interval-censored competing risks data
... for interval-censored ...the regression coefficients and the baseline ...of regression co- efficients and cumulative baseline hazard for current status data, which is the simplest form of ...
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Semiparametric regression on cumulative incidence function with interval-censored competing risks data
... the interval censoring may result in biased estimation of the cause-specific cumulative incidence function, an important quantity in the competing risk framework, used for evaluating interventions in populations, ...
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New approach to interval linear regression
... The tolerance quotient is easily interpreted by a user; It can used as a fitness measure of the model; Outliers are easy to detect and handle. Future work[r] ...
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Interval Estimate for Specific Points in Polynomial Regression
... the interval estimate for specific points in polynomial regression: zero of a linear regres- sion, abscissa of the extreme of a quadratic regression, abscissa of the inflection point of a cubic ...
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