Name
Abstract | ||
|---|---|---|
The minimum estimation variance (MEV) spatial sampling strategy is compared with some further strategies based on systematic designs and the sample mean. Since in environmental surveys data are usually collected repeatedly in time at sites whose selection is based on practical circumstances only, it seems worth measuring the efficiency of spatial sampling strategies through the expectation of design mean square errors under several superpopulation models assumed about the fixed population generating process. Relating the study to specific superpopulations, MEV efficiencies can be calculated and a quantitative evaluation is made possible by the use of scenario analyses for several sample sizes and different models of spatial drift and correlations. The MEV strategy revealed itself to be the relatively more efficient one under realistic conditions of nonstationary spatial drifts and bounded sample sizes. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.csda.2004.10.010 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
spatial sequential sampling,nonstationary spatial drift,different model,mev efficiency,fixed population generating process,environmental surveys data,spatial drift,sample size,superpopulation model,mev strategy,bounded sample size,mev spatial,spatial sampling strategy,spatial dependence,scenario analysis,efficiency evaluation,environmental survey,mean square error,sequential sampling,survey data | Econometrics,Population,Spatial dependence,Spatial correlation,Survey sampling,Mean squared error,Scenario analysis,Sampling (statistics),Statistics,Sample size determination,Mathematics | Journal |
Volume | Issue | ISSN |
50 | 3 | Computational Statistics and Data Analysis |
Citations | PageRank | References |
3 | 1.03 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giovanni Lafratta | 1 | 4 | 2.09 |