A Weighted Exponential Model for Grouped Line Transect Data

Likelihood-based inference for clustered line transect data

The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference is implemented using Markov chain Monte Carlo (MCMC) methods to obtain efficient estimates of spatia...

Estimations on the Generalized Exponential Distribution Using Grouped Data

A Correlated Worker Model for Grouped, Imbalanced and Multitask Data

We consider the important crowdsourcing problem of estimating worker confusion matrices, or sensitivities and specificities for binary classification tasks. In addition to providing diagnostic insights into worker performance, such estimates enable robust online task routing for classification tasks exhibiting imbalance and asymmetric costs. However, labeled data is often expensive and hence es...

Adaptive line transect sampling.

Adaptive line transect sampling offers the potential of improved population density estimation efficiency over conventional line transect sampling when populations are spatially clustered. In adaptive sampling, survey effort is increased when areas of high animal density are located, thereby increasing the number of observations. Its disadvantage is that the survey effort required is not known ...

Grouped Data Exponentially Weighted Moving Average Control Charts

In the manufacture of metal fasteners in a progressive die operation, and other industrial situations, important quality dimensions cannot be measured on a continuous scale, and parts are classified into groups using a step gauge. This article proposes a version of exponentially weighted moving average (EWMA) control charts applicable to monitoring the grouped data for process shifts. The run l...