Results 241 to 250 of about 60,047 (288)

Two-Stage Negative Adaptive Cluster Sampling

Communications in Mathematics and Statistics, 2018
The authors deal with adaptive cluster sampling, a better alternative of the simple random sampling in cases when the population is rare and clustered. With this approach, auxiliary information is often used in order to overcome the problem with the increasing sample size.
Latpate, R. V., Kshirsagar, J. K.
exaly   +3 more sources

Adjusted two-stage adaptive cluster sampling

Applied Mathematics and Computation, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
A. Khan, Hassen A. Muttlak
exaly   +3 more sources

Ratio estimators in adaptive cluster sampling

Environmetrics, 2007
AbstractIn most surveys data are collected on many items rather than just the one variable of primary interest. Making the most use of the information collected is a issue of both practical and theoretical interest. Ratio estimates for the population mean or total are often more efficient.
Arthur L. Dryver, Chang‐Tai Chao
exaly   +2 more sources

Application of adaptive sampling in fishery part 2: Truncated adaptive cluster sampling designs [PDF]

, 2001
There are some experiences that researcher come across quite number of time for very large networks in the initial samples such that they cannot finish the sampling procedure. Two solutions have been proposed and used by marine biologists which we discuss in this article: i) Adaptive cluster sampling based on order statistics with a stopping rule, ii ...
Salehi, M.
core   +4 more sources

Adaptive survey designs for sampling rare and clustered populations [PDF]

Mathematics and Computers in Simulation, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jennifer A. Brown, Mohammad Salehi M., Mohammad Moradi 0002, Bardia Panahbehagh, David R. Smith   +4 more
openaire   +3 more sources

Adaptive Cluster Sampling

2021
While conducting a sample survey, a number of difficult sampling problems are encountered. One of them is the problem in estimating the population mean/total when it is rare or geographically uneven. If the population of interest is hidden or elusive, then it becomes difficult to identify it for sampling.
Raosaheb Latpate, Jayant Kshirsagar, Vinod Kumar Gupta, Girish Chandra   +3 more
openaire   +2 more sources

Adaptive cluster double sampling with post stratification with application to an epiphytic lichen community

Environmental and Ecological Statistics, 2017
The implementation of an adaptive cluster sampling design often becomes logistically challenging because variation in the final sampling effort introduces uncertainty in survey planning.
Stefano Antonio Gattone, Paolo Giordani, Tonio Di Battista   +2 more
exaly   +3 more sources

Inverse Adaptive Cluster Sampling

Biometrics, 2001
Consider a population in which the variable of interest tends to be at or near zero for many of the population units but a subgroup exhibits values distinctly different from zero. Such a population can be described as rare in the sense that the proportion of elements having nonzero values is very small.
Christman, Mary C., Lan, Feng
openaire   +2 more sources

Negative adaptive cluster sampling

Model Assisted Statistics and Applications, 2019
The traditional sampling methods such as simple random sampling, stratified sampling etc. cannot be used to study the rare and clustered populations. Such type of populations are frequently observed in ecological, environmental and social sciences. In such situations, often the auxiliary information is collected along with the variable of interest ...
R. V. Latpate, J. K. Kshirsagar
openaire   +1 more source

Adaptive Cluster Sampling in Two-stage Sampling

Australian & New Zealand Journal of Statistics, 2014
Summary: Adaptive cluster sampling can be a useful design for surveying rare and clustered populations. Here we present a new development in adaptive cluster sampling where we use a two-stage design and extend the complete allocation sampling method.
Moradi, Mohammad, Brown, Jennifer A., Guo, Weilong   +2 more
openaire   +1 more source