Optimal Sampling Design for Variables with Varying Spatial Importance

Determination of Optimal Sampling Design for Spatial Data Analysis

Extended Abstract. Inferences for spatial data are affected substantially by the spatial configuration of the network of sites where measurements are taken. Consider the following standard data-model framework for spatial data. Suppose a continuous, spatially-varying quantity, Z, is to be observed at a predetermined number, n, of points ....[ To Countinue Click here]

Sensitivity Analysis of Spatial Sampling Designs for Optimal Prediction

In spatial statistic, the data analyzed which is correlated and this correlation is due to their locations in the studied region. Such correlation that is related to distance between observations is called spatial correlation. Usually in spatial data analysis, the prediction of the amount of uncertain quantity in arbitrary 4locations of the area is considered according to attained observations ...

Economical Design of Double Variables Acceptance Sampling With Inspection Errors

The paper presents an economical model for double variable acceptance sampling with inspection errors. Taguchi cost function is used as acceptance cost while quality specification functions are normal with known variance. An optimization model is developed for double variables acceptance sampling scheme at the presence of inspection errors with either constant or monotone value functions. The m...

An Optimal Spatial Sampling Design for Social Surveys

Design of Economic Optimal Double Sampling Design with Zero Acceptance Numbers

  In zero acceptance number sampling plans, the sample items of an incoming lot are inspected one by one. The proposed method in this research follows these rules: if the number of nonconforming items in the first sample is equal to zero, the lot is accepted but if the number of nonconforming items is equal to one, then second sample is taken and the policy of zero acceptance number would be ap...