Results 241 to 250 of about 646,279 (275)

Bootstrap Confidence Intervals for Adaptive Cluster Sampling

Biometrics, 2000
Summary.Consider a collection of spatially clustered objects where the clusters are geographically rare. Of interest is estimation of the total number of objects on the site from a sample of plots of equal size. Under these spatial conditions, adaptive cluster sampling of plots is generally useful in improving efficiency in estimation over simple ...
Christman, Mary C., Pontius, Jeffrey S.
openaire   +2 more sources

Stratified Inverse Adaptive Cluster Sampling

2021
In forestry and environmental sciences, some species of plants and animals are rare and clustered, i.e., abundance of zeros. The traditional sampling methods provide poor estimates of the population mean/total. In such situations, adaptive sampling is useful.
Raosaheb Latpate, Jayant Kshirsagar, Vinod Kumar Gupta, Girish Chandra   +3 more
openaire   +1 more source

Generalized ratio-type and ratio-exponential-type estimators for population mean under modified Horvitz-Thompson estimator in adaptive cluster sampling

Journal of Statistical Computation and Simulation, 2019
In the present article, we propose the generalized ratio-type and generalized ratio-exponential-type estimators for population mean in adaptive cluster sampling (ACS) under modified Horvitz-Thompson estimator.
F. Younis, J. Shabbir
semanticscholar   +1 more source

Generalized estimator for the estimation of rare and clustered population variance in adaptive cluster sampling

Journal of Statistical Computation and Simulation, 2019
Adaptive cluster sampling (ACS) is considered to be the most suitable sampling design for the estimation of rare, hidden, clustered and hard-to-reach population units.
Muhammad Nouman Qureshi, Naureen Riaz, M. Hanif   +2 more
semanticscholar   +1 more source

Two-Stage Inverse Adaptive Cluster Sampling

2021
It is well known that if the population under study is homogeneous then one can assign equal probability of selection to the units in the population and can estimate the population parameters using the selected sample. But if the population has clumps in it then the equiprobable assignment may lead to poor estimates of the population parameters.
Raosaheb Latpate, Jayant Kshirsagar, Vinod Kumar Gupta, Girish Chandra   +3 more
openaire   +1 more source

Rare and clustered population estimation using the adaptive cluster sampling with some robust measures

Journal of Statistical Computation and Simulation, 2018
The use of robust measures helps to increase the precision of the estimators, especially for the estimation of extremely skewed distributions. In this article, a generalized ratio estimator is proposed by using some robust measures with single auxiliary ...
Muhammad Nouman Qureshi, Cem Kadılar, Muhammad Noor Ul Amin, M. Hanif   +3 more
semanticscholar   +1 more source

Generalized estimator for the estimation of clustered population mean in adaptive cluster sampling

, 2019
In many real-world survey situations, the use of auxiliary information together with the survey variable is very common phenomenon. The ratio and regression estimators are most commonly used estimation methods that incorporate the auxiliary information ...
Muhammad Nouman Qureshi, M. Hanif
semanticscholar   +1 more source

Adaptive sampling without replacement of clusters

Statistical Methodology, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dryver, Arthur L., Thompson, Steven K.
openaire   +1 more source

Estimation of rare and clustered population variance in adaptive cluster sampling

Communications in Statistics - Theory and Methods, 2018
Many researchers used auxiliary information together with survey variable to improve the efficiency of population parameters like mean, variance, total and proportion.
Muhammad Nouman Qureshi, Sadia Khalil, Chang‐Tai Chao, M. Hanif   +3 more
semanticscholar   +1 more source

Asymptotics in adaptive cluster sampling

Environmental and Ecological Statistics, 2003
In this article we consider asymptotic properties of the Horvitz-Thompson and Hansen-Hurwitz types of estimators under the adaptive cluster sampling variants obtained by selecting the initial sample by simple random sampling without replacement and by unequal probability sampling with replacement.
openaire   +1 more source