Standard factorial designs may sometimes be inadequate for experiments that aim to estimate a generalized linear model, for example, for describing a binary response in terms of several variables. A method is proposed for finding exact designs for such experiments which uses a criterion that allows for uncertainty in the link function, the linear predictor or the model parameters, together with...

This paper describes graphical methods for multiple-response data within the framework of the multivariate linear model (MLM), aimed at understanding what is being tested in a multivariate test, and how factor/predictor effects are expressed across multiple response measures. In particular, we describe and illustrate a collection of SAS macro programs for: (a) Data ellipses and low-rank biplots...

INTRODUCTION: Bacterial meningitis is a life-threatening illness resulting from bacterial infection of the meninges. In Cuba there are about 500 cases of bacterial meningitis every year. Still a little part of these cases is caused by the bacteria N. meningitidis as meningococcal disease (clinical forms: meningitis, septicaemia or both), despite the disease being under vaccination control since...

In the last decade several estimators have been proposed that enforce the grouping property. A regularized estimate exhibits the grouping property if it selects groups of highly correlated predictor rather than selecting one representative. The pairwise fused lasso is related to fusion methods but does not assume that predictors have to be ordered. By penalizing parameters and differences betwe...

In low bit-rate coders, the near-sample and far-sample redundancies of the speech signal are usually removed by a cascade of a shortterm and a long-term linear predictor. These two predictors are usually found in a sequential and therefore suboptimal approach. In this paper we propose an analysis model that jointly finds the two predictors by adding a regularization term in the minimization pro...

In this paper a geographical weighted pseudo empirical best linear unbiased predictor (GWEBLUP) for small area averages is proposed, and two approaches for estimating its mean squared error (MSE), a conditional approach and an unconditional one, are developed. The popular empirical best linear unbiased predictor (EBLUP) under the linear mixed model and its associated MSE estimator are obtained ...

This paper proposes a new variant of the least square autoregressive (LSAR) method for speech reconstruction, which can estimate via least squares a segment of missing samples by applying the linear prediction (LP) model of speech. First, we show that the use of a single high-order linear predictor can provide better results than the classic LSAR techniques based on shortand long-term predictor...

This paper presents a new method for characterizing brain responses in both PET and fMRI data. The aim is to capture the correlations between the scans of an experiment and a set of external predictor variables that are thought to aaect the scans, such as type, intensity, or shape of stimulus response. Its main feature is a Canonical Variates Analysis (CVA) of the estimated eeects of the predic...

In this paper, we describe a system to rank suspected answers to natural language questions. We process both corpus and query using a new technique, predictive annotation, which augments phrases in texts with labels anticipating their being targets of certain kinds of questions. Given a natural language question, our IR system returns a set of matching passages, which we then rank using a linea...

Regression diagnostics are geared toward identifying individual points or groups of points that have an important influence on a fitted model. When fitting a model with survey data, the sources of influence are the response variable Y, the predictor variables X, and the survey weights, W. This article discusses the use of the hat matrix and leverages to identify points that may be influential i...