• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.397-408
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• 2018

Various methods for accurate parameter estimation have been developed in a sample survey and it is also common to use a ratio estimator or the regression estimator using auxiliary information. The ratio-type estimator has been used in many recent studies and is known to improve the accuracy of estimation by adjusting the ratio estimator. However, various studies are under way to solve it since the ratio-type estimator is biased. In this study, we propose a generalized ratio-type estimator with a new parameter added to the ratio-type estimator to remove the bias. We suggested a method to apply this result to the parameter estimation under the error assumption of heteroscedasticity. Through simulation, we confirmed that the suggested generalized ratio-type estimator gives good results compared to conventional ratio-type estimators.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.655-664
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• 2015

A nonresponse adjusted raking ratio estimator that consists of weighting adjustment using estimated response probability and raking procedure is often used to reduce the nonresponse bias and keep the calibration property of the estimator. We investigated asymptotic properties of nonresponse adjusted raking ratio estimator and proposed a variance estimator. A simulation study is used to examine the performance of suggested estimators.

• Journal of the Korean Data and Information Science Society
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• v.5 no.2
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• pp.59-74
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• 1994

The hazard ratio may be useful as a descriptive measure to compare the hazard experience of a treatment group with that of a control group. In this paper, we propose a kernel estimator of hazard ratio with censored survival data. The uniform consistency and asymptotic normality of the proposed estimator are proved by using counting process approach. In order to assess the performance of the proposed estimator, we compare the kernel estimator with Cox estimator and the generalized rank estimators of hazard ratio in terms of MSE by Monte Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.13-24
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• 2001

In this paper, we investigated mean estimation methods in two-phase sampling. Under the fixed expected cost we reviewed the optimal sample sizes, minimum variances and approximate unbiased variance estimators for usual ratio estimator, stratified sample mean with proportional allocation and Rao's allocation of the second phase sample. Also we proposed combined ratio estimator, which uses both ratio estimation and stratification and derived optimal sample size, minimum variance and unbiased variance estimator. Through a limited simulation study, we compared estimators by design effects and came to know that ratio estimator is more efficient than stratified sample mean in some cases and inefficient in the other cases, but combined ratio estimator is more efficient than others in most cases.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.4
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• pp.32-38
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• 2006

In this paper a sequence estimator of CDMA communication system is suggested. A sequence estimator uses Galois Field operation. A sequence estimator can provide another CDMA pilot signal which is un-modulated spreaded signal. A estimated sequence signal and received signal have no correlation. Tow signals can be summed using MRC(maximal ratio combine) method. The stronger signal can be added as a larger ratio, but the weaker signal can be added as a smaller ratio. We can distinguish strong signal using SNR estimator. Therefore it is possible to receive an additional pilot signal, and to support more reliable communications by using sequence estimator.

• Communications for Statistical Applications and Methods
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• v.23 no.1
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• pp.47-55
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• 2016

Stratified cluster sampling has been widely used for effective parameter estimations due to reductions in time and cost. The probability proportional to size (PPS) sampling method is used when the number of cluster element are significantly different. However, simple random sampling (SRS) is commonly used for simplicity if the number of cluster elements are almost the same. Also it is known that the ratio estimator produces a good performance when the total number of population elements is known. However, the two stage cluster estimator should be used if the total number of elements in population is neither known nor accurate. In this study we suggest a composite estimator by combining the ratio estimator and the two stage cluster estimator to obtain a better estimate under a certain population circumstance. Simulation studies are conducted to compare the superiority of the suggested estimator with two other estimators.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.663-671
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• 2012

In the present study, a combined ratio cum regression estimator is proposed to estimate the population mean of the study variable in the presence of a non-response using an auxiliary variable under double sampling. The expressions of bias and mean squared error(MSE) based on the proposed estimator is derived under double (or two stage) sampling to the first degree of approximation. Some estimators are also derived from the proposed class by allocating the suitable values of constants used. A comparison of the proposed estimator with the usual unbiased estimator and other derived estimators is carried out. An empirical study is carried out to demonstrate the performance of the suggested estimator and of others; it is endow that the empirical results backing the theoretical study.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1029-1039
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• 2006

There are different kinds of methods to estimate the odds ratio for unemployment statistics in small areas, namely, the composite estimator, the Woolf estimator and the Mantel-Haenszel estimator. We can compare the reliability of these estimators according to the bias and MSE. The estimation procedures considered by this study have been applied to estimate the bias and MSE of the odds ratio between the male and female unemployment rate in some small areas. The Woolf estimator or the Mantel-Haenszel estimator is more stable than the composite estimator, but all these three estimators are similar to each other from the aspect of efficiency.

• Journal of the Korean Statistical Society
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• v.9 no.2
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• pp.181-193
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• 1980

A class of nonparametric estimators of the ratio of scale parameters is proposed. The estimators are based on the distribution-free rank-like test suggested by Fligner and Killeen (1976). An explicit form of the estimator is the median of the ratios of absolute deviations from the combined sample median. A small-sample Monte Carlo study shows that the proposed estimator is more efficient than the Bhattacharyya (1977) estimator. The proposed estimator is is reasonably insensitive to small failures in the assumption of equal medians. A modified estimator is also considered when the meidans are unequal.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.255-269
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• 2017

This article explores the analysis of longitudinal surveys in which same units are investigated on several occasions. Multivariate exponential ratio type estimator has been proposed for the estimation of the finite population median at the current occasion in two occasion longitudinal surveys. Information on several additional auxiliary variables, which are stable over time and readily available on both the occasions, has been utilized. Properties of the proposed multivariate estimator, including the optimum replacement strategy, are presented. The proposed multivariate estimator is compared with the sample median estimator when there is no matching from a previous occasion and with the exponential ratio type estimator in successive sampling when information is available on only one additional auxiliary variable. The merits of the proposed estimator are justified by empirical interpretations and validated by a simulation study with the help of some natural populations.