In this work we establish the first linear convergence result for the stochastic heavy ball method. The method performs SGD steps with a fixed stepsize, amended by a heavy ball momentum term. In the analysis, we focus on minimizing the expected loss and not on finite-sum minimization, which is typically a much harder problem. While in the analysis we constrain ourselves to quadratic loss, the o...

We consider frailty models for clustered survival data in the presence of measurement errors in covariates. We Ž rst show that when the measurement error is accounted for in a full likelihood analysis but the distribution of the unobserved covariate is misspeciŽ ed, the maximum likelihood estimators are asymptotically biased, especially for the variance component, whose bias can be substantial....

In this paper, we examine rst and second order asymptotic theory for two estima-tors in a linear quantile model in the case where the response is observed multiple times at xed covariate vectors x 1 ; ; x k. The rst estimator is the regression quantile esti-mator introduced by Koenker and Bassett (1978) while the second estimator is a least squares estimator on the sample quantiles of the respo...

Given data y and k covariates x one problem in linear regression is to decide which in any of the covariates to include when regressing y on the x. If k is small it is possible to evaluate each subset of the x. If however k is large then some other procedure must be use. Stepwise regression and the lasso are two such procedures but they both assume a linear model with error term. A different ap...

To detect sustainable changes in the production processes, memory-type control charts are frequently utilized. This study is conducted to assess performance of Bayesian adaptive exponentially weighted moving average (AEWMA) chart using ranked set sampling schemes following two different loss functions presence a measurement error for posterior and predictive distributions conjugate priors. base...

This paper introduces a model to make decision on the maintenance of a mechanical component subject to condition monitoring. A stochastic model is used to determine what maintenance action should be taken at a monitoring check and the follow up inspection times. The condition of component has a stochastic relation with measurements. A new state space model is developed and used, to predict the ...

In many environmental epidemiology studies, the locations and/or times of exposure measurements and health assessments do not match. In such settings, health effects analyses often use the predictions from an exposure model as a covariate in a regression model. Such exposure predictions contain some measurement error as the predicted values do not equal the true exposures. We provide a framewor...

Abstract Road casualties represent an alarming concern for modern societies. During the last years, several authors proposed sophisticated approaches to help authorities implement new policies. These models were usually developed considering a set of socio-economic variables and ignoring measurement error, which can bias statistical inference. This paper presents Bayesian model analyse car cras...

Objective: The objective of the study was to perform a Non linear mixed-effects analysis of the pharmacokinetics of clopidogrel, to study the effect of covariates like age, body surface area and creatinine clearance on the population pharmacokinetics of clopidogrel in South Indian Cardiac patients. Methods: A simple, rapid and sensitive isocratic HPLC-UV method for detection and quantification ...

In this paper, a framework for the analysis of the error-reject trade-off in linearly combined classifiers is proposed. We start from a framework developed by Tumer and Ghosh [1,2]. We extend this framework and analyse some hypotheses under which the linear combination of classifier outputs can improve the error-reject trade-off of the individual classifiers. Experiments that support some of th...