Multi-phased designs and biased sampling designs are two of the well recognized approaches to enhance study efficiency. In this paper, we propose a new and cost-effective sampling design, the two-phase probability dependent sampling design (PDS), for studies with a continuous outcome. This design will enable investigators to make efficient use of resources by targeting more informative subjects...

Utility functions in Bayesian experimental design are usually based on the posterior distribution. When the posterior is found by simulation, it must be sampled from for each future dataset drawn from the prior predictive distribution. Many thousands of posterior distributions are often required. A popular technique in the Bayesian experimental design literature, which rapidly obtains samples f...

MOTIVATION Systems biology employs mathematical modelling to further our understanding of biochemical pathways. Since the amount of experimental data on which the models are parameterized is often limited, these models exhibit large uncertainty in both parameters and predictions. Statistical methods can be used to select experiments that will reduce such uncertainty in an optimal manner. Howeve...

The optimum experimental design for systems following the ®rst-order Arrhenius model under linearly increasing temperature pro®les was studied by determining the sampling conditions that lead to a minimum con®dence region of the model parameters. It was found that experiments should be started at the lowest possible temperature and, for each initial temperature, there is an optimal heating rate...

A new methodology is introduced for spatial sampling design when the variable of interest cannot be directly observed, but information on it can be obtained by sampling a related variable, and estimation of the underlying model is required. An approach based on entropy has been proposed by Bueso, Angulo, and Alonso (1998, Environ. Ecol. Statist. 5, No. 1, 29 44) in the case where a model for th...

In this paper, a non-uniform sampling algorithm is proposed for one-dimensional bandlimited time varying signals. The main feature of the proposed sampling scheme is that the sampling steps are inversely proportional to signal gradient or slope of the signal. As a result, a smaller sampling step is obtained whenever the gradient is high and vice-versa. Thus, a better representation of the signa...

Various sampling techniques are widely used in environmental, social and resource surveys. Spatial sampling techniques are more efficient than conventional sampling when surveying spatially distributed targets such as CO2 emissions, soil pollution, a population distribution, disaster distribution, and disease incidence, where spatial autocorrelation and heterogeneity are prevalent. However, des...

OBJECTIVES To explore classification rules based on data mining methodologies which are to be used in defining strata in stratified sampling of healthcare providers with improved sampling efficiency. METHODS We performed k-means clustering to group providers with similar characteristics, then, constructed decision trees on cluster labels to generate stratification rules. We assessed the varia...

.......................................................................................................................................... v Introduction ..................................................................................................................................... 1 Objectives ...................................................................................................