• Title/Summary/Keyword: 복합추정 가중값

Search Result 6, Processing Time 0.017 seconds

Composite estimation type weighting adjustment for bias reduction of non-continuous response group in panel survey (패널조사에서 비연속 응답 그룹 편향 보정을 위한 복합가중값)

  • Choi, Hyunga;Kim, Youngwon
    • The Korean Journal of Applied Statistics
    • /
    • v.32 no.3
    • /
    • pp.375-389
    • /
    • 2019
  • Sample attrition according to a long-term tracking reduces the representativeness of the sample data in a panel study. Most panel surveys in South Korea and other countries have prepared response adjustment weights in order to solve problems regarding representativeness due to sample attrition. In this paper, we divided the panel data into continuous response group and non-continuous response group according to response patterns and considered a weighting adjustment method to reduce the bias of the non-continuous response group. A simulation indicated that the proposed composite estimation type weighting method, which reflected the characteristics of non-continuous response groups, could be more efficient than other weighting methods in terms of reducing non-response bias. As a case study, the proposed methods are applied to the Korean Longitudinal Study of Ageing (KLoSA) data of the Korea Employment Information Service.

General Regression Estimators in Survey Sampling (표본조사에서 일반회귀 추정량의 활용)

  • Kim, Kyu-Seong
    • Survey Research
    • /
    • v.5 no.2
    • /
    • pp.49-70
    • /
    • 2004
  • This paper is a broad review about general regression estimators, which are very useful when auxiliary variables are available in survey sampling. We investigate the process of development of general regression estimators from birth to suggestion of variance estimation method and examine some properties of general regression estimators by comparing with calibration and QR estimators. We also present some forms of general regression estimators available under complex sampling designs such as stratified sampling and cluster sampling. Finally, we comment some advantages as well as disadvantages of general regression estimators and theoretical and practical development in the future.

  • PDF

융합기술 가치평가 모형의 개발에 관한 연구

  • Seong, Tae-Eung;Jeon, Seung-Pyo;Park, Hyeon-U
    • Proceedings of the Korea Technology Innovation Society Conference
    • /
    • 2017.05a
    • /
    • pp.175-192
    • /
    • 2017
  • 4차 산업혁명의 도래와 더불어 ICT 기계, ICT 금융, ICT 의료, ICT 나노 등과 같이 기술분야별 영역의 장벽이 허물어지고, 학제간 연구(Interdisplinary Research)가 일상화됨에 따라 무형자산의 가치평가시에도 융합기술의 가치평가 모형에 대한 니즈가 증대되고 있다. 특히, 기술의 매매, 현물출자, 기술금융(투자유치, 담보 보증), 인수 합병, 청산 소송 등 다양한 용도로 사용되고 있는 기술가치평가 모형은 융합기술의 입력변수 결정에 대한 체계적인 로직을 제공하지 못하고 있는 실정이다. 일반적으로 실제 거래사례가 존재할 경우, 국제가치평가기준(IVS)에 의하면 시장접근법이 우선적으로 적용될 수 있다고 권고된다. 그러나 융합기술의 이전거래를 비롯한 평가 활용사례를 수집하기도 어렵고 그렇다할 평가모델이 존재하지 않는 것이 사실이다. 융합기술에 대한 기술 및 시장의 사업화 환경을 고려하는 경우 소득접근법 기반의 평가기법이 유용하게 활용될 수 있는데, 기술수명, 매출액추정, 할인율, 산업기술요소 등의 핵심변수 결정에 관한 정형화된 로직이 존재하지 않으므로 본 고에서 융합기술 사례에 대해 실용적으로 활용가능한 변수추정 로직을 제시하고자 한다. 기술수명의 경우, 복수 개의 국제특허분류(IPC)별 피인용특허수에 따라 가중 적용하여 수명 추정을 위한 기준값을 정하며, 사업화소요기간 및 비용의 경우 평가대상 융합기술이 속하는 업종별 메타데이터값을 가중평균하여 현금흐름 추정기간을 최종 도출할 수 있다. 소득접근법에서의 매출추정, 할인율, 산업기술요소 변수 추정 이외에도 로열티공제법 적용을 위한 로열티율 결정에 있어서, 융합기술이 응용가능한 산업(업종)별 매출액 기반으로 가중 적용하여 각 변수값을 산출할 수 있다. 본 연구에서 개발된 융합기술 가치평가 모형은 향후 기술의 융복합화 특성을 반영하여 적정 가치를 산출하는 평가 가이드라인을 제공할 수 있을 것으로 기대된다.

  • PDF

Geostatistical Integration of Multi-Geophysical Data Measured at Different Ranges (측정 범위가 다른 다중 물리 탐사 자료의 지구통계학적 복합 해석)

  • Oh, Seok-Hoon
    • Geophysics and Geophysical Exploration
    • /
    • v.12 no.4
    • /
    • pp.309-315
    • /
    • 2009
  • Integrated interpretation of multi-geophysical data has been continuously used in terms that it has provided more confident information than the result from single-geophysical data. Especially, geostatistical integration has its own superiority that it is possible to deal with spatial characteristics as well as physical properties of survey data and the process of integration is clear. This paper further extends the previous work of geostatistical inversion for integrated interpretation. In this paper, we propose a new way of dealing with the case that the multi-geophysical data do not share the measurement range. According to the geostatistical kriging, the closer between the measurement points, the smaller kriging variance we get, and vice versa. We used this spatial properties as a weighting value to the process of geostatistical inversion for the geophysical data integration. An objective way to integrate different kinds of geophysical data measured at different ranges is provided with this algorithm.

Speech Enhancement Based on Mixture Hidden Filter Model (HFM) Under Nonstationary Noise (혼합 은닉필터모델 (HFM)을 이용한 비정상 잡음에 오염된 음성신호의 향상)

  • 강상기;백성준;이기용;성굉모
    • The Journal of the Acoustical Society of Korea
    • /
    • v.21 no.4
    • /
    • pp.387-393
    • /
    • 2002
  • The enhancement technique of noise signal using mixture HFM (Midden Filter Model) are proposed. Given the parameters of the clean signal and noise, noisy signal is modeled by a linear state-space model with Markov switching parameters. Estimation of state vector is required for estimating original signal. The estimation procedure is based on mixture interacting multiple model (MIMM) and the estimator of speech is given by the weighted sum of parallel Kalman filters operating interactively. Simulation results showed that the proposed method offers performance gains relative to the previous results with slightly increased complexity.

Foreground Extraction and Depth Map Creation Method based on Analyzing Focus/Defocus for 2D/3D Video Conversion (2D/3D 동영상 변환을 위한 초점/비초점 분석 기반의 전경 영역 추출과 깊이 정보 생성 기법)

  • Han, Hyun-Ho;Chung, Gye-Dong;Park, Young-Soo;Lee, Sang-Hun
    • Journal of Digital Convergence
    • /
    • v.11 no.1
    • /
    • pp.243-248
    • /
    • 2013
  • In this paper, depth of foreground is analysed by focus and color analysis grouping for 2D/3D video conversion and depth of foreground progressing method is preposed by using focus and motion information. Candidate foreground image is generated by estimated movement of image focus information for extracting foreground from 2D video. Area of foreground is extracted by filling progress using color analysis on hole area of inner object existing candidate foreground image. Depth information is generated by analysing value of focus existing on actual frame for allocating depth at generated foreground area. Depth information is allocated by weighting motion information. Results of previous proposed algorithm is compared with proposed method from this paper for evaluating the quality of generated depth information.