• Communications for Statistical Applications and Methods
• /
• v.20 no.4
• /
• pp.247-257
• /
• 2013

A variety of practical problems can be addressed in the framework of rotation (successive) sampling. The present work presents a sample rotation pattern where sampling units are drawn on two successive occasions. The problem of estimation of population variance on current (second) occasion in two - occasion successive (rotation) sampling has been considered. A class of estimators has been proposed for population variance that includes many estimators as a particular case. Asymptotic properties of the proposed class of estimators are discussed. The proposed class of estimators is compared with the sample variance estimator when there is no matching from the previous occasion. Optimum replacement policy is discussed. Results are supported with the empirical means of comparison.

• Journal of the Korean Statistical Society
• /
• v.35 no.4
• /
• pp.343-353
• /
• 2006

The two-way balanced one-level rotation design, $r_1^m-r_2^{m-1}$, and the three-way balanced multi-level rotation design, $r_1^m(\iota)-r_1^{m-1}$, were discussed (Park et al., 2001, 2003). Although these rotation designs enjoy balancing properties, they have a restriction of $r_2=c{\cdot}r_1$ (c should be a integer value) which interferes with applying these designs freely to various situations. To overcome this difficulty, we extend the $r_1^m(\iota)-r_1^{m-1}$ design to new one under the most general rotation system. The new multi-level rotation design also satisfies tree-way balancing which is done on interview time, rotation group and recall time. We present the rule and rotation algorithm which guarantee the three-way balancing. In particular, we specify the necessary condition for the extended three-way balanced multi-level rotation sampling design.

• Journal of the Korean Statistical Society
• /
• v.29 no.1
• /
• pp.45-62
• /
• 2000

Rotation design is a sampling technique to reduce response burden and to estimate the population characteristics varying in time. Park and Kim(1999) discussed a generation of one-level rotation design which is called as {{{{r_1^m ~-r_2^m-1}}}} design has more applicable form than existing before. In the structure of {{{{r_1^m ~-r_2^m-1}}}} design, we derive the exact variances of generalized composite estimators for level, change and aggregate level characteristics of interest, and optimal coefficients minimizing their variances. Finally numerical examples are shown by the efficiency of alternative designs relative to widely used 4-8-4 rotation design. This is continuous work of Part Ⅰ studied by Park and Kim(1999).

• Communications for Statistical Applications and Methods
• /
• v.22 no.5
• /
• pp.445-462
• /
• 2015

This article deals with the problem of estimation of the population mean in presence of multi-auxiliary information in two occasion rotation sampling. A multivariate exponential ratio type estimator has been proposed to estimate population mean at current (second) occasion using information on p-additional auxiliary variates which are positively correlated to study variates. The theoretical properties of the proposed estimator are investigated along with the discussion of optimum replacement strategies. The worthiness of proposed estimator has been justified by comparing it to well-known recent estimators that exist in the literature of rotation sampling. Theoretical results are justified through empirical investigations and a detailed study has been done by taking different choices of the correlation coefficients. A simulation study has been conducted to show the practicability of the proposed estimator.

• Journal of the Korean Statistical Society
• /
• v.32 no.2
• /
• pp.175-191
• /
• 2003

An empirical Bayesian approach is discussed for estimation of characteristics from the two-way balanced rotation sampling design which includes U.S. Current Population Survey and Canadian Labor Force Survey as special cases. An empirical Bayesian estimator is derived for monthly effect under presence of two types of biases and correlations It is shown that the marginal distribution of observation provides more general correlation structure than that frequentist has assumed. Consistent estimators are derived for hyper-parameters in Normal priors.

• Proceedings of the Korean Association for Survey Research Conference
• /
• 2002.11a
• /
• pp.255-274
• /
• 2002

We classify rotation sampling designs into two classes. The first class replaces sample units within the same rotation group while the second class replaces sample units between different rotation groups. The first class is specified by the three-way balanced design which is a multi-level version of previous balanced designs. We introduce an extended generalized composite estimator (EGCE) and derive its variance and mean squared error for each of the two classes of design, cooperating two types of correlations and three types of biases. Unbiased estimators are derived for difference between interview time biases, between recall time biases, and between rotation group biases. Using the variance and mean squared error, since any rotation design belongs to one of the two classes and the EGCE is a most general estimator for rotation design, we evaluate the efficiency of EGCE to simple weighted estimator and the effects of levels, design gaps, and rotation patterns on variance and mean squared error.

• Journal of the Korean Statistical Society
• /
• v.32 no.3
• /
• pp.245-259
• /
• 2003

The 2-way balanced one-level rotation design has been discussed (Park et al., 2001), where the 2-way balancing is done on interview time in monthly sample and rotation group. We extend it to 3-way balanced multi-level design to obtain more information of the same sample unit for one or more previous months. The 3-way balancing is accomplished not only on interview time in monthly sample and rotation group but also on recall time as well. The 3-way balancing eliminates or reduces any bias arising from unbalanced interview time, rotation group and recall time, and all rotation groups are equally represented in the monthly sample. We present the rule and rotation algorithm which guarantee the 3-way balancing. In particular, we specify the necessary and sufficient condition for the 3-way balanced multi-level rotation design.

• The Korean Journal of Applied Statistics
• /
• v.17 no.1
• /
• pp.61-73
• /
• 2004

Rotation sampling designs may be classified into two categories. The first type uses the same sample unit for the entire life of the survey. The second type uses the sample unit only for a fixed number of times. In both type of designs, the entire sample is partitioned into a finite number(=G) of rotation groups. This paper is generalization of the first type designs. Since the generalized design can be identified by only G rotation groups and recall level 1, we denote this rotation system as l/G rotation design. Under l/G rotation design, variance and mean squared error (MSE) of generalized composite estimator are derived, incorporating two type of biases and exponentially decaying correlation pattern. Compromising MSE's of some selected l/G designs, we investigate design efficiency, design gap effect, ans the effects of correlation and bias.

• Proceedings of the Korean Statistical Society Conference
• /
• 2002.05a
• /
• pp.19-24
• /
• 2002

The two-way balanced one-level rotation design has been discussed (Park, Kim and Choi, 2001), where the two-way balancing is done on interview time in monthly sample and rotation group. We extend it to three-way balanced multi-level design under the most general rotation system. The three-way balancing is accomplished on interview time not only in monthly sample and rotation group but also in recall time. We present the necessary condition and rotation algorithm which guarantee the three-way balancing. We propose multi-level composite estimators (MCE) from this design and derive their variances and mean squared errors (MSE), assuming the correlation from the measurements of the same sample unit and three types of biases in monthly sample.

• Journal of the Korean Statistical Society
• /
• v.2 no.1
• /
• pp.17-23
• /
• 1973

No Abstract, See Full Text