• 제목/요약/키워드: Statistics Matching

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성향 점수를 이용한 퍼지 매칭 방법: IBM SPSS 22 Ver. (FUZZY matching using propensity score: IBM SPSS 22 Ver.)

  • 김소연;백종일
    • Journal of the Korean Data and Information Science Society
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    • 제27권1호
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    • pp.91-100
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    • 2016
  • 성향점수 매칭이란 선택편의가 존재 할 수 있는 두 집단의 데이터를 성향 점수로 매칭하여 비슷한 성향을 갖는 데이터를 추출하는 방법이다. 본 논문은 그 중 하나인 퍼지 매칭 방법을 제시하였다. 성향 점수를 만들기 위해 통제변수를 선정하는 방법과 로지스틱 회귀분석을 통하여 성향 점수를 구하는 방법을 제시하였으며, 이 점수로 퍼지 매칭을 통해 성향이 비슷한 실험 집단과 통제 집단을 추출할 수 있었다. 본 논문에서는 허용오차 범위를 달리하여 분포도와 표준화 차이를 통해 두 집단이 동일한 집단임을 증명했으며, 허용오차 범위 점수가 작아질수록 선택되어 지는 케이스 수도 작아지는 것을 확인 할 수 있었다.

Note on Properties of Noninformative Priors in the One-Way Random Effect Model

  • Kang, Sang Gil;Kim, Dal Ho;Cho, Jang Sik
    • Communications for Statistical Applications and Methods
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    • 제9권3호
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    • pp.835-844
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    • 2002
  • For the one-way random model when the ratio of the variance components is of interest, Bayesian analysis is often appropriate. In this paper, we develop the noninformative priors for the ratio of the variance components under the balanced one-way random effect model. We reveal that the second order matching prior matches alternative coverage probabilities up to the second order (Mukerjee and Reid, 1999) and is a HPD(Highest Posterior Density) matching prior. It turns out that among all of the reference priors, the only one reference prior (one-at-a-time reference prior) satisfies a second order matching criterion. Finally we show that one-at-a-time reference prior produces confidence sets with expected length shorter than the other reference priors and Cox and Reid (1987) adjustment.

PPD: A Robust Low-computation Local Descriptor for Mobile Image Retrieval

  • Liu, Congxin;Yang, Jie;Feng, Deying
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제4권3호
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    • pp.305-323
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    • 2010
  • This paper proposes an efficient and yet powerful local descriptor called phase-space partition based descriptor (PPD). This descriptor is designed for the mobile image matching and retrieval. PPD, which is inspired from SIFT, also encodes the salient aspects of the image gradient in the neighborhood around an interest point. However, without employing SIFT's smoothed gradient orientation histogram, we apply the region based gradient statistics in phase space to the construction of a feature representation, which allows to reduce much computation requirements. The feature matching experiments demonstrate that PPD achieves favorable performance close to that of SIFT and faster building and matching. We also present results showing that the use of PPD descriptors in a mobile image retrieval application results in a comparable performance to SIFT.

Noninformative Priors for the Coefficient of Variation in Two Inverse Gaussian Distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Communications for Statistical Applications and Methods
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    • 제15권3호
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    • pp.429-440
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    • 2008
  • In this paper, we develop the noninformative priors when the parameter of interest is the common coefficient of variation in two inverse Gaussian distributions. We want to develop the first and second order probability matching priors. But we prove that the second order probability matching prior does not exist. It turns out that the one-at-a-time and two group reference priors satisfy the first order matching criterion but Jeffreys' prior does not. The Bayesian credible intervals based on the one-at-a-time reference prior meet the frequentist target coverage probabilities much better than that of Jeffreys' prior. Some simulations are given.

Estimation of Geometric Mean for k Exponential Parameters Using a Probability Matching Prior

  • Kim, Hea-Jung;Kim, Dae Hwang
    • Communications for Statistical Applications and Methods
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    • 제10권1호
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    • pp.1-9
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    • 2003
  • In this article, we consider a Bayesian estimation method for the geometric mean of $textsc{k}$ exponential parameters, Using the Tibshirani's orthogonal parameterization, we suggest an invariant prior distribution of the $textsc{k}$ parameters. It is seen that the prior, probability matching prior, is better than the uniform prior in the sense of correct frequentist coverage probability of the posterior quantile. Then a weighted Monte Carlo method is developed to approximate the posterior distribution of the mean. The method is easily implemented and provides posterior mean and HPD(Highest Posterior Density) interval for the geometric mean. A simulation study is given to illustrates the efficiency of the method.

BAYESIAN INFERENCE FOR FIELLER-CREASY PROBLEM USING UNBALANCED DATA

  • Lee, Woo-Dong;Kim, Dal-Ho;Kang, Sang-Gil
    • Journal of the Korean Statistical Society
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    • 제36권4호
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    • pp.489-500
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    • 2007
  • In this paper, we consider Bayesian approach to the Fieller-Creasy problem using noninformative priors. Specifically we extend the results of Yin and Ghosh (2000) to the unbalanced case. We develop some noninformative priors such as the first and second order matching priors and reference priors. Also we prove the posterior propriety under the derived noninformative priors. We compare these priors in light of how accurately the coverage probabilities of Bayesian credible intervals match the corresponding frequentist coverage probabilities.

Developing Noninformative Priors for the Common Mean of Several Normal Populations

  • Kim, Yeong-Hwa;Sohn, Eun-Seon
    • Journal of the Korean Data and Information Science Society
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    • 제15권1호
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    • pp.59-74
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    • 2004
  • The paper considers the Bayesian interval estimation for the common mean of several normal populations. A Bayesian procedure is proposed based on the idea of matching asymptotically the coverage probabilities of Bayesian credible intervals with their frequentist counterparts. Several frequentist procedures based on pivots and P-values are introduced and compared with Bayesian procedure through simulation study. Both simulation results demonstrate that the Bayesian procedure performs as well or better than any available frequentist procedure even from a frequentist perspective.

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ON CORRELATION MATCHING APPROACH TO BLIND SEPARATION OF NONSTATIONARY SOURCES

  • Choi, Seung-Jin;Hong, Heon-Seok;Oh, Jun-Whan
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -1
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    • pp.241-244
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    • 2000
  • This paper addresses a new method of blind source separation (BSS) when sources are nonstationary signals. Our method requires only multiple correlation matrices of the observed data at several time-windowed data frames to estimate the mixing matrix. In contrast to most existing BSS methods where higher-order statistics is necessary, our method is based on only second-order statistics. In the framework of correlation matching, we develop a new BSS algorithm. The useful behavior of the proposed method is verified by numerical experiments.

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도시공원 면적이 유아 행복감에 미치는 영향에 대한 인과관계 연구 (Causal effect of urban parks on children's happiness)

  • 권나연;김찬민
    • 응용통계연구
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    • 제36권1호
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    • pp.63-83
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    • 2023
  • 기존의 많은 연구에서 도시공원을 비롯한 녹지와 유아 행복감 간에 유의미한 상관관계를 도출했다. 또한 이를 통해 간접적으로 도시공원의 면적/근접성이 유아기의 행복감 증진에 효과가 있을 것이라 유추하였다. 하지만 관찰된 자료를 통한 인과효과 추정은 교란 변수의 적절한 조정을 필요로하고, 이런 관점에서 도시공원의 면적과 유아 행복감의 인과관계는 명확히 밝혀지지 않았다고 할 수 있다. 본 연구에서는 한국아동패널 자료를 이용하여 도시공원의 면적이 유아 행복감에 미치는 영향에 대한 인과효과를 추정하였다. 교란 변수를 조정하기 위한 방법으로 회귀 모형을 이용한 조정(regression adjustment), 가중치 기법(weighting), 그리고 매칭(matching) 등을 이용하였고, 각 방법들의 중요 개념을 분석 결과에 앞서 기술하였다. 교란 변수의 선택에 있어서 유향 비순환 그래프(directed acyclic graph)를 사용하였다. 분석 결과, 기존의 상관관계를 이용한 결론과는 다르게 도시공원의 면적과 유아 행복감 간에는 유의미한 인과효과가 존재하지 않았다.

Analysis of a Targeted Intervention Programme on the Risk Behaviours of Injecting Drug Users in India: Evidence From the National Integrated Biological and Behavioural Surveillance Survey

  • Sahu, Damodar;Ranjan, Varsha;Chandra, Nalini;Nair, Saritha;Kumar, Anil;Arumugam, Elangovan;Rao, Mendu Vishnu Vardhana
    • Journal of Preventive Medicine and Public Health
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    • 제55권4호
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    • pp.407-413
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    • 2022
  • Objectives: This study provides insights on the impact of a targeted intervention (TI) programme on behaviour change among injecting drug users (IDUs) in India. Methods: This paper examined the data from the Integrated Biological and Behavioural Surveillance 2014-2015 for IDUs in India. Logistic regression was performed to understand the factors (TI programme services) that affected injecting risk behaviours by adjusting for covariates. Propensity score matching was conducted to understand the impact of the TI programme on using new needles/syringes and sharing needles/syringes in the most recent injecting episode by accounting for the covariates that predicted receiving the intervention. Results: Participants who received new needles and syringes from peer educators or outreach workers were 1.3 times (adjusted odds ratio, 1.29; 95% confidence interval [CI], 1.09 to 1.53) more likely to use new needles/syringes during most recent injecting episode than participants who did not receive needles/syringes. The matched-samples estimate (i.e., average treatment effect on treated) of using new needles in the most recent injecting episode showed a 2.8% (95% CI, 0.0 to 5.6) increase in the use of new needles and a 6.5% (95% CI, -9.7 to -3.3) decrease in needle sharing in the most recent injecting episode in participants who received new needles/syringes. There was a 2.2% (95% CI, -3.8 to -0.6) decrease in needle sharing in the most recent injecting episode among participants who were referred to other services (integrated counselling and testing centre, detox centres, etc.). Conclusions: The TI programme proved to be effective for behaviour change among IDUs, as substantiated by the use of new needles/syringes and sharing of needles/syringes.