Estimating mortality from times-at-large: testing accuracy and precision using simulated single tag-recovery data

Estimating Accuracy from Unlabeled Data

We consider the question of how unlabeled data can be used to estimate the true accuracy of learned classifiers. This is an important question for any autonomous learning system that must estimate its accuracy without supervision, and also when classifiers trained from one data distribution must be applied to a new distribution (e.g., document classifiers trained on one text corpus are to be ap...

Estimating and Testing Fundamental Stock Prices: Evidence from Simulated Economies

1 We thank Lisa Kramer for helpful comments and the Social Sciences and Humanities Research Council of Canada for financial support.

High-Accuracy Elevation Data at Large Scales from Airborne Single-Pass SAR Interferometry

Digital elevation models (DEMs) are essential data sets for disaster risk management and humanitarian relief services as well as many environmental process models. At present, on the one hand, globally available DEMs only meet the basic requirements and for many services and modeling studies are not of high enough spatial resolution and lack accuracy in the vertical. On the other hand, LiDAR-DE...

Estimating causal effects from large data sets using propensity scores.

The aim of many analyses of large databases is to draw causal inferences about the effects of actions, treatments, or interventions. Examples include the effects of various options available to a physician for treating a particular patient, the relative efficacies of various health care providers, and the consequences of implementing a new national health care policy. A complication of using la...

AccucheckInform II: About Its Accuracy and Precision