• Title/Summary/Keyword: sampling stage

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Korean women wage analysis using selection models (표본 선택 모형을 이용한 국내 여성 임금 데이터 분석)

  • Jeong, Mi Ryang;Kim, Mijeong
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.5
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    • pp.1077-1085
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    • 2017
  • In this study, we have found the major factors which affect Korean women's wage analysing the data provided by 2015 Korea Labor Panel Survey (KLIPS). In general, wage data is difficult to analyze because random sampling is infeasible. Heckman sample selection model is the most widely used method for analysing the data with sample selection. Heckman proposed two kinds of selection models: the one is the model with maximum likelihood method and the other is the Heckman two stage model. Heckman two stage model is known to be robust to the normal assumption of bivariate error terms. Recently, Marchenko and Genton (2012) proposed the Heckman selectiont model which generalizes the Heckman two stage model and concluded that Heckman selection-t model is more robust to the error assumptions. Employing the two models, we carried out the analysis of the data and we compared those results.

A Study on the Stage of Change in Exercise Behaviors, Exercise Self Efficacy, Depression and Stress in Middle Aged Women (중년여성의 운동행위 변화단계, 운동 자기효능감, 우울 및 스트레스에 관한 연구)

  • Lee, Yun-Mi;Park, Hyoung-Sook
    • Women's Health Nursing
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    • v.10 no.3
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    • pp.218-225
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    • 2004
  • Purpose: The study was performed to identify exercise self-efficacy, depression, and stress by the stage of change in exercise behavior in middle aged women. Method: The subjects consisted of 317 women residing in B city by convenience sampling. The collected data was analyzed by the SPSS/WIN program. Result: The subjects were distributed in each stage of exercise behavior change: There were 53 subjects in the pre-contemplation stage, 86 subjects in the contemplation stage, 88 subjects in the preparation stage, 51 subjects in the action stage and 39 subjects in the maintenance stage. Analysis of variance showed that exercise self-efficacy (F=39.9, p<.001), depression (F=5.58, p<.001), and stress (F=6.33, p<.001) were significantly associated with the stages of exercise behavior change. There was a significant negative correlation between the stage of change and depression, and the stage of change and stress, but a significant positive correlation between the stage of change and self- efficacy, depression and stress. Conclusion: This study identified that exercise self-efficacy, depression and stress were significant variables to explain a possible relationship with exercise stages of middle aged women. This study provides new information to influence the development of better health promotion and exercise intervention for middle aged women in the community.

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Sensitivity Approach of Sequential Sampling Using Adaptive Distance Criterion (적응거리 조건을 이용한 순차적 실험계획의 민감도법)

  • Jung, Jae-Jun;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.9 s.240
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    • pp.1217-1224
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    • 2005
  • To improve the accuracy of a metamodel, additional sample points can be selected by using a specified criterion, which is often called sequential sampling approach. Sequential sampling approach requires small computational cost compared to one-stage optimal sampling. It is also capable of monitoring the process of metamodeling by means of identifying an important design region for approximation and further refining the fidelity in the region. However, the existing critertia such as mean squared error, entropy and maximin distance essentially depend on the distance between previous selected sample points. Therefore, although sufficient sample points are selected, these sequential sampling strategies cannot guarantee the accuracy of metamodel in the nearby optimum points. This is because criteria of the existing sequential sampling approaches are inefficient to approximate extremum and inflection points of original model. In this research, new sequential sampling approach using the sensitivity of metamodel is proposed to reflect the response. Various functions that can represent a variety of features of engineering problems are used to validate the sensitivity approach. In addition to both root mean squared error and maximum error, the error of metamodel at optimum points is tested to access the superiority of the proposed approach. That is, optimum solutions to minimization of metamodel obtained from the proposed approach are compared with those of true functions. For comparison, both mean squared error approach and maximin distance approach are also examined.

An Algorithm of Minimum Bandpass Sampling Selection with Guard-band Between Down-converted Adjacent IF signals (하향변환된 인접 IF신호간의 보호대역을 고려한 최소 대역통과 샘플링 주파수 선택 알고리즘)

  • Bae, Jung-Hwa;Cho, Jae-Wan;Ko, Yong-Chae;Cac, Tran Nguyen;Park, Jin-Woo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.12A
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    • pp.1286-1295
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    • 2007
  • This paper proposes, based on a bandpass sampling theory, a novel method to find valid sampling frequency range and minimum sampling rate with low computational complexity for downconversion of N bandpass radio frequency(RF) signals, under application of all possible signal placements(full permutations) in a IF stage. Additionally, we have developed a complexity-reducing method to obtaine the opttimal and minimal sampling rate for supporting the user-wanted guard-band or spacing between adjacent downconverted signal spectrums. Moreover, we have verified through comparisons with other methods that the proposed methods have more advantageous properties.

Development of Ingrowth Estimation Equations for Pinus densiflora in Korea Derived from National Forest Inventory Data (국가산림자원조사 자료를 이용한 소나무의 진계생장 추정식 개발)

  • Moon, Ga Hyun;Yim, Jong Su;Shin, Man Yong
    • Journal of Korean Society of Forest Science
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    • v.107 no.4
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    • pp.402-411
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    • 2018
  • This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.

Bayesian Approach to the Prediction in the Censored Sample from Rayleigh Population

  • Ko, Jeong-Hwan;Kim, Young-Hoon;Kang, Sang-Gil
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.1
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    • pp.71-77
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    • 1997
  • S independent sample 0,1,2, $\cdots$, s-1 (or stages 0,1,2, $\cdots$, s-1) are available from the Raleigh population. Procedure for predicting any order statistic in the $(s+1)^{th}$ sample is developed by obtaining the predictive distribution at stage s. Bounds for the sample size at stage S, in order to have the variance at stage S less than that at stage (s-1), are obtained.

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The Three-Stage Cluster Unrelated Question Model

  • Ahn, Seung-Chul;Lee, Gi-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.55-65
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    • 2003
  • In this study, we systemize the theoretical validity for applying unrelated question model to three-stage cluster sampling method and derive the estimate and it's variance of sensitive parameter. We derive the minimum variance form under the optimal values of the subsample sizes when the cost are fixed. Under the some given precision, we obtain the optimal values of the subsample sizes and derive the minimum cost form by using them.

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Heart Beat Interval Estimation Algorithm for Low Sampling Frequency Electrocardiogram Signal (낮은 샘플링 주파수를 가지는 심전도 신호를 이용한 심박 간격 추정 알고리즘)

  • Choi, Byunghun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.7
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    • pp.898-902
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    • 2018
  • A novel heart beat interval estimation algorithm is presented based on parabola approximation method. This paper presented a two-step processing scheme; a first stage is finding R-peak in the Electrocardiogram (ECG) by Shannon energy envelope estimator and a secondary stage is computing the interpolated peak location by parabola approximation. Experimental results show that the proposed algorithm performs better than with the previous method using low sampled ECG signals.

The Statistical Model for Predicting Flood Frequency

  • Noh, Jae-Sik;Lee, Kil-Choon
    • Korean Journal of Hydrosciences
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    • v.4
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    • pp.51-63
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    • 1993
  • This study is to verify the applicability of statistical models in predicting flood frequency at the stage gaging stations of which the flow is under natural condition in the Han River basin. The results of the study show that the statistical flood frequency models were proven to be fairly reasonable to apply in practice, and also were compared with sampling variance to calibrate the statistical efficiency of the estimators of the T year floods Q(T) by two different flood frequency models. As a result, it was showed that for return periods greater than about T = 10 years the annual exceedance series estimators of Q(T) has smaller sampling variance than the annual maximum series estimators. It was showed that for the range of return periods the partial duration series estimators of !(T) has smaller sampling variance than the annual maximum series estimate only if the POT model contains at least 2N(N : record length) items or more in order to estimate Q(T) more efficiently than the ANNMAX model.

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Unrelated question model with quantitative attribute by stratified double sampling (층화이중추출법에 의한 양적속성의 무관질문모형)

  • 이기성;홍기학
    • The Korean Journal of Applied Statistics
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    • v.8 no.1
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    • pp.27-38
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    • 1995
  • In the surveys of sensitive issues of the population that is composed of several unknown-size stratum, we propose the unrelated question model with quantitative attribute by using stratified double sampling. And, we consider two types of sample allocations under the fixed cost, which are the proportional allocation, the optimum allocation. In efficiency, the proosed model is inferior to the unrelated question model with quantitative attribute by stratified sampling in case of the size of each stratum is known. But we find that efficiency of the proposed model is increased, when the selecting probability of sensitive question p is small and first stage sample size n' is large.

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