To classify time series by nearest neighbors, we need to specify or learn one or several distance measures. We consider variations of the Mahalanobis distance measures which rely on the inverse covariance matrix of the data. Unfortunately—for time series data—the covariance matrix has often...

We develop an approach, based on multiple imputation, that estimates the marginal survival distribution in survival analysis using auxiliary variables to recover information for censored observations. To conduct the imputation, we use two working proportional hazards models to define an imputing...

El impacto de la intensidad del conflicto armado colombiano sobre el desarrollo social no ha sido cuantificado rigurosamente. Este documento busca avanzar en el análisis de los efectos sociales de la actividad armada ilegal en los últimos años, a través del examen de la evolución de...

This letter considers the problem of estimating expected values of functions that are inversely weighted by an unknown density using the k-Nearest Neighbor method. L²-consistency is established. The proposed estimator is also shown to be asymptotically semiparametric efficient. Some limited...

Several evaluations have been conducted to assess the impact of agricultural input subsidies in Malawi but have been mostly either descriptive or qualitatively inferred of the intervention impacts on the overall goal of the subsidy program. In most studies cited in this paper their approaches do...

Case-based reasoning (CBR) is a problem-solving paradigm that uses past experiences to solve new problems. Nearest neighbor is a common CBR algorithm for retrieving similar cases, whose similarity function is sensitive to irrelevant attributes. Taking the relevancy of the attributes into account...

This article discusses a model designed to help sales representatives acquire customers in a business-to-business environment. Sales representatives are often overwhelmed by available information, so they use arbitrary rules to select leads to pursue. The goal of the proposed model is to...

This letter considers the problem of estimating expected values of functions that are inversely weighted by an unknown density using the k-Nearest Neighbor method. L²-consistency is established. The proposed estimator is also shown to be asymptotically semiparametric efficient. Some limited...