• Title/Summary/Keyword: population estimation technique

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Population persistence of the perennial kelp Eisenia arborea varies across local spatial scales

  • Gossard, Daniel J.;Steller, Diana L.
    • ALGAE
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    • v.37 no.1
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    • pp.63-74
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    • 2022
  • Perennial stipitate kelps are globally distributed and individual species can inhabit broad latitudinal ranges, expressing notably longevous persistence. Despite the foundational role kelps provide to their communities, little is known about the variability in persistence of the stipitate kelps at local spatial scales. We studied the population persistence of Eisenia arborea, a heat- and wave force-tolerant perennial stipitate kelp with a distributional range extending from British Columbia to south of the range limit of all other northeast Pacific kelps, in Baja California Sur, Mexico. Persistence characteristics for E. arborea among sites were compared and used to test the hypothesis that stand persistence varied at local spatial scales around Isla Natividad, a Pacific island off the Baja California peninsula with documented spatiotemporal environmental heterogeneity. Collected individuals around the island were "aged" using the previously validated age estimation technique of counting annual cortical dark rings. After detecting no significant differences among sites in the covariation between estimated ages for collected individuals and stipe length, we utilized in-situ population-level stipe length measurements to more rapidly predict age structures within six stands around the island. Predicted age structures, and associated stand densities, revealed persistence characteristics and density varied at local scales and a strong positive relationship existed between stand density and stand mean and maximum ages. We speculate that stands responded differently to deterministic influences (e.g., the 2014-2016 marine heatwave and / or competition with Macrocystis) resulting in heterogenous local persistence of this foundation species.

A Study on the Estimation Technique of Area Source Emissions for Air Pollution Prediction (大氣汚染豫測을 위한 面汚染源排出量 算定模型의 開發에 關한 硏究)

  • 박준대;김정욱
    • Journal of Korean Society for Atmospheric Environment
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    • v.6 no.1
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    • pp.43-50
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    • 1990
  • In the estimation of grid type area source emissions, the factors by which emissions are distributed spatially must be considered comprehensively. The estimation process can be approached systematically by connecting the emission activity of air pollutants with land use pattern and the various impacts can be taken into account in the process by using such area information as land use, population, distribution of households, types of housing units, fuel consumption and so on. The estimation procedure was computerized in order to calculate area source emissions by grid information system. This computerization helped to augment effectiveness and efficiency not only by managing enormous data but also by performing diverse functions.

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A response probability estimation for non-ignorable non-response

  • Chung, Hee Young;Shin, Key-Il
    • Communications for Statistical Applications and Methods
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    • v.29 no.2
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    • pp.263-275
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    • 2022
  • Use of appropriate technique for non-response occurring in sample survey improves the accuracy of the estimation. Many studies have been conducted for handling non-ignorable non-response and commonly the response probability is estimated using the propensity score method. Recently, post-stratification method to obtain the response probability proposed by Chung and Shin (2017) reduces the effect of bias and gives a good performance in terms of the MSE. In this study, we propose a new response probability estimation method by combining the propensity score adjustment method using the logistic regression model with post-stratification method used in Chung and Shin (2017). The superiority of the proposed method is confirmed through simulation.

Performance of Spiked Population Models for Spectrum Sensing

  • Le, Tan-Thanh;Kong, Hyung-Yun
    • Journal of electromagnetic engineering and science
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    • v.12 no.3
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    • pp.203-209
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    • 2012
  • In order to improve sensing performance when the noise variance is not known, this paper considers a so-called blind spectrum sensing technique that is based on eigenvalue models. In this paper, we employed the spiked population models in order to identify the miss detection probability. At first, we try to estimate the unknown noise variance based on the blind measurements at a secondary location. We then investigate the performance of detection, in terms of both theoretical and empirical aspects, after applying this estimated noise variance result. In addition, we study the effects of the number of SUs and the number of samples on the spectrum sensing performance.

Small Area Estimation Techniques Based on Logistic Model to Estimate Unemployment Rate

  • Kim, Young-Won;Choi, Hyung-a
    • Communications for Statistical Applications and Methods
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    • v.11 no.3
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    • pp.583-595
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    • 2004
  • For the Korean Economically Active Population Survey(EAPS), we consider the composite estimator based on logistic regression model to estimate the unemployment rate for small areas(Si/Gun). Also, small area estimation technique based on hierarchical generalized linear model is proposed to include the random effect which reflect the characteristic of the small areas. The proposed estimation techniques are applied to real domestic data which is from the Korean EAPS of Choongbuk. The MSE of these estimators are estimated by Jackknife method, and the efficiencies of small area estimators are evaluated by the RRMSE. As a result, the composite estimator based on logistic model is much more efficient than others and it turns out that the composite estimator can produce the reliable estimates under the current EAPS system.

Recalibration Estimation for Unit Nonresponse at the Two Levels Auxiliary Information

  • Yum, Joon Keun;Son, Chang Kyoon;Jeung, Young Mee
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.665-678
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    • 2003
  • In this paper we suggest the new calibration estimator, which is called to the recalibration estimator, and its variance estimator using two-phase sampling technique according to the auxiliary information having strong correlation with the variable of interest under the unit nonresponse. In this unit nonresponse situation, an available information may exists at the level of whole population or the first-phase sample. The proposed recalibration estimator derives from the first and second phase weights respectively.

ON COMPARISON OF PERFORMANCES OF SYNTHETIC AND NON-SYNTHETIC GENERALIZED REGRESSION ESTIMATIONS FOR ESTIMATING LOCALIZED ELEMENTS

  • SARA AMITAVA
    • Journal of the Korean Statistical Society
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    • v.34 no.1
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    • pp.73-83
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    • 2005
  • Thompson's (1990) adaptive cluster sampling is a promising sampling technique to ensure effective representation of rare or localized population units in the sample. We consider the problem of simultaneous estimation of the numbers of earners through a number of rural unorganized industries of which some are concentrated in specific geographic locations and demonstrate how the performance of a conventional Rao-Hartley-Cochran (RHC, 1962) estimator can be improved upon by using auxiliary information in the form of generalized regression (greg) estimators and then how further improvements are also possible to achieve by adopting adaptive cluster sampling.

Optimal field synthesis for enhancing the modeling capabilities of reservoir/aquifer fields

  • Jang, Min-Chul;Choe, Jong-Geun
    • 한국지구물리탐사학회:학술대회논문집
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    • 2003.11a
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    • pp.684-689
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    • 2003
  • One field identified by an inverse method is one of multiple candidate solutions those are independently obtained through a specific estimation technique. While averaging of optimized fields can provide a better description of the spatial feature of an unknown field, it deteriorates the flow and transport characteristics of the optimized fields. As a result, the averaged field is not suited for modeling aquifer performances. Based on genetic algorithm, an optimal field synthesis technique is developed, which combines diversely optimized fields into a refined group of fields. Each field in the population is paired, and a sub-region of each field is exchanged by crossover operation to create a group of synthesized fields of enhanced modeling capability. The population of the fields is evolved till the synthesized fields become sufficiently similar. Applications of the optimal field synthesis to synthetic cases indicate that the objective functions of the fields assessing the modeling capabilities are further reduced after the optimal field synthesis. The identified fields from various inverse techniques may yield a range of modeling results under varied flow situations. The uncertainty is narrowed down through the optimal field synthesis and the associated modeling results converge on that of the reference field. The developed inverse modeling facilitates the construction of a reliable simulation model and hence trustworthy predictions of the future performances.

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Studies on probability extinction of Peregrine falcon species wintering around Jang Hang wetlands in the Han river (겨울철 한강 장항습지에 서식하는 매 멸종확률 예측에 대한 연구)

  • LEE, Sangdon
    • Journal of Wetlands Research
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    • v.18 no.3
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    • pp.282-285
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    • 2016
  • Peregrine falcon (Falco peregrinus) are listed as endangered species and Natural monument #323 in Korea, and this study examined the possibility of extinct of peregrine falcon in Jang Hang wetland near Han river using with the application of Population Viability Analysis (PVA) technique. In Jang Hang wetland areas population was monitored during 1999-2005 averaging 10.8 individuals and PVA analysis was done for the 5 years (2015-2020) using the average population size. Using the initial population was estimated 20% of extinct rate during the time. This estimation was quite low considering water pollution and loss of habitat. Also PVA only used population size lacking in other life history information. Nonetheless falcon population can be in risk of extinction if the current construction of crossovers in the river, cement bank are maintained. Long term information regarding life history needs essential.

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.