One-Step Targeted Minimum Loss-based Estimation Based on Universal Least Favorable One-Dimensional Submodels

One-Step Targeted Minimum Loss-based Estimation Based on Universal Least Favorable One-Dimensional Submodels.

Consider a study in which one observes n independent and identically distributed random variables whose probability distribution is known to be an element of a particular statistical model, and one is concerned with estimation of a particular real valued pathwise differentiable target parameter of this data probability distribution. The targeted maximum likelihood estimator (TMLE) is an asympto...

One - Dimensional Least - Squares Model - Based Halftoning

A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model of visual perception. It produces a halftoned image that minimizes the squared error between the response of the visual model to the original image and the response of the printer and visual models to the halftoned image. For one-dimensional halftoning, where each column is proce...

Balancing Score Adjusted Targeted Minimum Loss-based Estimation.

Adjusting for a balancing score is sufficient for bias reduction when estimating causal effects including the average treatment effect and effect among the treated. Estimators that adjust for the propensity score in a nonparametric way, such as matching on an estimate of the propensity score, can be consistent when the estimated propensity score is not consistent for the true propensity score b...

Development of a rapid, one-step-visual method to detect Salmonella based on IC-LAMP method

Background: Salmonella can cause serious human gastroenteritis and is frequently isolated from various food samples. The cell culturing, immunoassay, and polymerase chain reactions (PCR) are the current methods to detect such pathogenic agents. However, these methods are time-consuming and labor-intensive, and thus unavailable for rapid-monitoring of Salmonella</em...

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