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On the regression analysis of tumour recurrence rates

Statistics in Medicine, 1989
AbstractRegression models with mixture (random) components are proposed for the statistical analysis of recurrent events when waiting times between successive events are unknown. These models allow adjustment of parameter estimates for unobserved heterogeneity in the population (due for example to missing covariates) or overdispersion resulting from ...
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A regression method for modelling geometric rates

Statistical Methods in Medical Research, 2015
The occurrence of an event of interest over time is often summarized by the incidence rate, defined as the average number of events per person-time. This type of rate applies to events that may occur repeatedly over time on any given subject, such as infections, and Poisson regression represents a natural regression method for modelling the effect of ...
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The Analysis of Rates Using Poisson Regression Models

Biometrics, 1983
Models are considered in which the underlying rate at which events occur can be represented by a regression function that describes the relation between the predictor variables and the unknown parameters. Estimates of the parameters can be obtained by means of iteratively reweighted least squares (IRLS).
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Rate of convergence of the density estimation of regression residual

Statistics & Risk Modeling, 2013
Abstract Consider the regression problem with a response variable Y and with a d-dimensional feature vector X. For the regression function m(x) = E{Y|X = x}, this paper investigates methods for estimating the density of the residual Y − m(X) from independent and identically distributed data. If the density is twice differentiable and has
Györfi, László, Walk, Harro
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On Convergence Rates of Convex Regression in Multiple Dimensions

INFORMS Journal on Computing, 2014
We consider a least squares estimator for estimating a convex function f*: [0, 1]d → ℝ with bounded subgradients. A rate at which the sum of squared differences between the estimator and the true function f* converges to zero is computed. This work sheds light on computing the convergence rate of the multidimensional convex regression estimator.
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Rates and Poisson regression

2008
Epidemiological studies often involve the calculation of rates, typically rates of death or incidence rates of a chronic or acute disease. This is based upon counts of events occurring within a certain amount of time. The Poisson regression method is often employed for the statistical analysis of such data. However, data that are not actually counts of
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Quantile regression for rating teams

Statistical Modelling, 2007
Quantile regression is proposed for modeling game out comes and as the basis for rating teams. The model includes the standard location model for team strength as a special case, while allowing for a richer specification in which teams differ according to the quantiles of the out come distribution.
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Regression Rates Study of Mixed Hybrid Propellants

Journal of Propulsion and Power, 2005
The low regression rates of classic hybrid rocket fuels lead to large internal ports that limit potential applications. This experimental study investigated the increase in regression rate that results from adding a solid oxidizer and a catalyst to a hybrid fuel grain.
Robert Frederick   +3 more
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The Accuracy of Teachers’ Ratings of Ability: A Regression Model

American Educational Research Journal, 1985
Teachers’ rating of academic ability in mathematics and English were regressed on test scores in a sample of second grade students (n = 694 in mathematics, n = 736 in English). Fitted equations were interpreted as judgmental models of the rating process, and normative subjective probabilities were assigned to individual ratings, showing the extent to ...
Owen Egan, Peter Archer
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An Allocation Rule with Wealth‐Regressive Tax Rates

Journal of Public Economic Theory, 2002
We introduce a public good allocation rule whose direct implementation by asking agents their endowments leads to Nash equilibrium outcomes—always Pareto dominating voluntary contributions outcomes. Although the Nash equilibrium allocations induced by this rule are not Pareto optimal in general, they are so in two‐person economies.
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