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Threshold Gradient Descent Regularization in the Additive Risk Model with
, 2005
"... Summary An additive risk model is a useful alternative to the Cox model (Cox, 1972) and may be adopted when the absolute effects, instead of the relative effects, of multiple predictors on the hazard function are of interest. In this article, we propose using the threshold gradient descent regulariz ..."
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Summary An additive risk model is a useful alternative to the Cox model (Cox, 1972) and may be adopted when the absolute effects, instead of the relative effects, of multiple predictors on the hazard function are of interest. In this article, we propose using the threshold gradient descent
SEMIPARAMETRIC ADDITIVE RISKS MODEL FOR INTERVALCENSORED DATA
, 2006
"... Abstract: Intervalcensored event time data often arise in medical and public health studies. In such a setting, the exact time of the event of interest cannot be observed and is only known to fall between two monitoring times. Our interest focuses on the estimation of the effect of risk factors on ..."
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Cited by 3 (0 self)
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on intervalcensored data under the semiparametric additive hazards model. A nonparametric stepfunction is used to characterize the baseline hazard function. The covariate coefficients are estimated by maximizing the observed likelihood function, and their variances are obtained using the profile likelihood
2004): “The Additive Risk Model for Purchase Timing
 Marketing Science
"... proposed by Cox (1972), the ARM incorporates the effects of covariates on the individual hazard function in an additive (as opposed to multiplicative) manner. While a large number of previous studies on interpurchase timing have dealt with the question of correctly specifying the parametric distribu ..."
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proposed by Cox (1972), the ARM incorporates the effects of covariates on the individual hazard function in an additive (as opposed to multiplicative) manner. While a large number of previous studies on interpurchase timing have dealt with the question of correctly specifying the parametric
Checking a SemiParametric Additive Risk Model
"... ABSTRACT. McKeague & Sasieni (1994) propose a restriction of Aalen’s additive risk model by the additional hypothesis that some of the covariates have timeindependent influence on the intensity of the observed counting process. We introduce goodness of fit tests for this partly parametric Aale ..."
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ABSTRACT. McKeague & Sasieni (1994) propose a restriction of Aalen’s additive risk model by the additional hypothesis that some of the covariates have timeindependent influence on the intensity of the observed counting process. We introduce goodness of fit tests for this partly parametric
LASSO method for additive risk models with high dimensional covariates
, 2005
"... Summary. The additive risk model is a useful alternative to the proportional hazards model. It postulates that the hazard function is the sum of the baseline hazard function and the regression function of covariates. In this article, we investigate estimation in the additive risk model with right ce ..."
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Cited by 3 (2 self)
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Summary. The additive risk model is a useful alternative to the proportional hazards model. It postulates that the hazard function is the sum of the baseline hazard function and the regression function of covariates. In this article, we investigate estimation in the additive risk model with right
Identifying a Timedependent Covariate Effect in the Additive Risk Model
"... this article we adapt Murphy's [14] procedure to identify a timedependent covariate effect in the partly parametric additive risk model. We divide the time axis into segments and then compute a normalized loglikelihood ratio statistic based on piecewise constant regression functions on these ..."
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this article we adapt Murphy's [14] procedure to identify a timedependent covariate effect in the partly parametric additive risk model. We divide the time axis into segments and then compute a normalized loglikelihood ratio statistic based on piecewise constant regression functions
PROBABILITY AND MATHEMATICAL STATISTICS EMPIRICAL LIKELIHOOD FOR THE ADDITIVE RISK MODEL
"... ~ b s t r a c t. In this article, we investigate the empirical likelihood method for the additive risk model when the failure times are subject to lefttruncation and rightcensoring, An empuical likelihood ratio for the pvector of regression coefficients is defined and it is shown that its limitin ..."
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~ b s t r a c t. In this article, we investigate the empirical likelihood method for the additive risk model when the failure times are subject to lefttruncation and rightcensoring, An empuical likelihood ratio for the pvector of regression coefficients is defined and it is shown that its
Additive Logistic Regression: a Statistical View of Boosting
 Annals of Statistics
, 1998
"... Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms can often be dramatically improved by sequentially applying them to reweighted versions of the input dat ..."
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Cited by 1750 (25 self)
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data, and taking a weighted majority vote of the sequence of classifiers thereby produced. We show that this seemingly mysterious phenomenon can be understood in terms of well known statistical principles, namely additive modeling and maximum likelihood. For the twoclass problem, boosting can
Noise Trader Risk in Financial Markets
, 1989
"... We present a simple overlapping generations model of an asset market in which irrational noise traders with erroneous stochastic beliefs both affect prices and earn higher expected returns. The unpredictability of noise traders ’ beliefs creates a risk in the price of the asset that deters rational ..."
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Cited by 894 (25 self)
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We present a simple overlapping generations model of an asset market in which irrational noise traders with erroneous stochastic beliefs both affect prices and earn higher expected returns. The unpredictability of noise traders ’ beliefs creates a risk in the price of the asset that deters rational
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