• Title/Summary/Keyword: Successive occasion sampling

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A Class of Estimators for Population Variance in Two Occasion Rotation Patterns

  • Singh, G.N.;Priyanka, Priyanka;Prasad, Shakti;Singh, Sarjinder;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.20 no.4
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    • pp.247-257
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    • 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.

Regression Estimators with Unequal Selection Probabilities on Two Successive Occasions

  • Kim, Kyu-Seong
    • Journal of the Korean Statistical Society
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    • v.25 no.1
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    • pp.25-37
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    • 1996
  • In this paper, we propose regression estimators based on a partial replacement sampling scheme over two successive occasions and derive the minimum variances of them. PPSWR, RHC, $\pi$PS and PPSWOR schemes are considered to select unequal probability samples on two occasions. Simulation results over four populations are given for comparison of composite estimators and regression estimators.

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Markov Chain Monte Carol estimation in Two Successive Occasion Sampling with Radomized Response Model

  • Lee, Kay-O
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.211-224
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    • 2000
  • The Bayes estimation of the proportion in successive occasions sampling with randomized response model is discussed by means of Acceptance Rejection sampling. Bayesian estimation of transition probabilities in two successive occasions is suggested via Markov Chain Monte Carlo algorithm and its applicability is represented in a numerical example.

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A study on unequal probability sampling over two successive occasions in time series (시계열 계속 표본조사에서 불균등확률 추출법 연구)

  • 박홍래;이계오
    • The Korean Journal of Applied Statistics
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    • v.6 no.1
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    • pp.145-162
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    • 1993
  • We review sampling schemes on successive occasions with partial replacement of units and propose a Rao-Hartley-Cochran(RHC) type's sampling scheme over two successive occasions with probability proportionate to observations on the previous occasion. For comparison of the reviewed and proposed sampling schemes, optimal estimator of population mean on second occasion and its variance are derived. The relative efficiency of the proposed sampling scheme is compared with other equal and unequal probability sampling scheme by theoretical and numerical simulation study. For simulation study, three artificial populations are generated by a time series model. It is observed that RHC type's sampling scheme has small variance and deviation in general.

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Multivariate analysis of longitudinal surveys for population median

  • Priyanka, Kumari;Mittal, Richa
    • 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.

Multivariate Rotation Design for Population Mean in Sampling on Successive Occasions

  • Priyanka, Kumari;Mittal, Richa;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.22 no.5
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    • pp.445-462
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    • 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.

Item sum techniques for quantitative sensitive estimation on successive occasions

  • Priyanka, Kumari;Trisandhya, Pidugu
    • Communications for Statistical Applications and Methods
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    • v.26 no.2
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    • pp.175-189
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    • 2019
  • The problem of the estimation of quantitative sensitive variable using the item sum technique (IST) on successive occasions has been discussed. IST difference, IST regression, and IST general class of estimators have been proposed to estimate quantitative sensitive variable at the current occasion in two occasion successive sampling. The proposed new estimators have been elaborated under Trappmann et al. (Journal of Survey Statistics and Methodology, 2, 58-77, 2014) as well as Perri et al. (Biometrical Journal, 60, 155-173, 2018) allocation designs to allocate long list and short list samples of IST. The properties of all proposed estimators have been derived including optimum replacement policy. The proposed estimators have been mutually compared under the above mentioned allocation designs. The comparison has also been conducted with a direct method. Numerical applications through empirical as well as simplistic simulation has been used to show how the illustrated IST on successive occasions may venture in practical situations.

Quantile Estimation in Successive Sampling

  • Singh, Housila P.;Tailor, Ritesh;Singh, Sarjinder;Kim, Jong-Min
    • Proceedings of the Korean Association for Survey Research Conference
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    • 2006.12a
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    • pp.67-83
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    • 2006
  • In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.

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QUANTILE ESTIMATION IN SUCCESSIVE SAMPLING

  • Singh, Housila P.;Tailor, Ritesh;Singh, Sarjinder;Kim, Jong-Min
    • Journal of the Korean Statistical Society
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    • v.36 no.4
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    • pp.543-556
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    • 2007
  • In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.