이중차분분석의 ‘금지된 비교’ 넘어서기: 이중차분분석의 최신 동향을 반영한 산정특례제도 효과 분석

김진환 한국보건경제정책학회 2022 보건경제와 정책연구 Vol.28 No.4

Difference-in-difference (DID) analysis is the most widely used research design to evaluate policy effects on public health. Recent literature poses the risk of forbidden comparison, which occurs when heterogeneities of treatment effects between time and population groups. The estimates of DID using a Two-way fixed effect estimator (TWFE) tend to be biased. The TWFE estimate is the sum of the variance-weighted average of the average treatment effect of the treated (VWATT), the variance-weighted average of parallel trend (VWPT), and the variation within the treatment effect (△ATT) over time. Research design, which includes a long post-treatment period as a treatment period, can capture the lag of policy effects and increase the data. Because of its usefulness, it is necessary to review the research design in a way that captures the treatment effect at multiple time points with a single coefficient and to identify the estimation problem in the process. In this study, the recent development in the DID was briefly reviewed, and the research design of the previous study was modified to explain the biasing of the estimates generated in the forbidden comparison. The estimates from TWFE should be interpreted with caution because the DID is not the same as TWFE. It is necessary to accurately identify the estimand to be estimated and connect it with the appropriate estimator. Efforts should be made to reevaluate the design and estimates of previously conducted studies based on the rapidly developing discussions on the DID and to improve the quality of future policy analysis studies.

A new extension of Lindley distribution: modified validation test, characterizations and different methods of estimation

Ibrahim, Mohamed,Yadav, Abhimanyu Singh,Yousof, Haitham M.,Goual, Hafida,Hamedani, G.G. The Korean Statistical Society 2019 Communications for statistical applications and me Vol.26 No.5

In this paper, a new extension of Lindley distribution has been introduced. Certain characterizations based on truncated moments, hazard and reverse hazard function, conditional expectation of the proposed distribution are presented. Besides, these characterizations, other statistical/mathematical properties of the proposed model are also discussed. The estimation of the parameters is performed through different classical methods of estimation. Bayes estimation is computed under gamma informative prior under the squared error loss function. The performances of all estimation methods are studied via Monte Carlo simulations in mean square error sense. The potential of the proposed model is analyzed through two data sets. A modified goodness-of-fit test using the Nikulin-Rao-Robson statistic test is investigated via two examples and is observed that the new extension might be used as an alternative lifetime model.

다중 프레임의 SAD를 이용한 드론 속도 측정

남돈호,염석원 한국융합신호처리학회 2019 융합신호처리학회 논문지 (JISPS) Vol.20 No.3

Drones are highly utilized because they can efficiently acquire long-distance videos. In drone operation, the speed, which is the magnitude of the velocity, can be set, but the moving direction cannot be set, so accurate information about the drone’s movement should be estimated. In this paper, we estimate the velocity of the drone moving at a constant speed and direction. In order to estimate the drone's velocity, the displacement of the target frame to minimize the sum of absolute difference (SAD) of the reference frame and the target frame is obtained. The ground truth of the drone’s velocity is calculated using the position of a certain matching point over all frames. In the experiments, a video was obtained from the drone moving at a constant speed at a height of 150 meters. The root mean squared error (RMSE) of the estimated velocities in x and y directions and the RMSE of the speed were obtained showing the reliability of the proposed method. 드론은 원거리 동영상을 효율적으로 획득할 수 있어서 활용성이 높다. 드론 운용에서 속도의 크기인 속력은 설정할 수 있지만 이동하는 방위의 정확한 값은 설정이 불가능하다. 본 논문에서는 드론에서 획득한 동영상을 이용하여 일정한 속도로 이동하는 드론의 속도를 추정한다. 기준 프레임과 표적 프레임의 Sum of Absolute Difference(SAD)를 최소로 하는 표적 프레임의 변위를 구한다. 드론의 실제 속도(Ground Truth)는 각 프레임에서 일정한 동일 지점(Matching Point)의 위치를 이용하여 계산한다. 실험에서 150m 상공에서 일정한 속력으로 이동하는 드론으로 동영상을 획득하였다. 추정한 x와 y방향의 속도와 속력의 평균 제곱근 오차(RMSE)를 구하여 제안한 방법의 신뢰성을 보였다.

On statistical properties of some difference-based error variance estimators in nonparametric regression with a finite sample

Chun Gun Park 한국데이터정보과학회 2011 한국데이터정보과학회지 Vol.22 No.3

We investigate some statistical properties of several difference-based error variance estimators in nonparametric regression model. Most of existing difference-based methods are developed under asymptotical properties. Our focus is on the exact form of mean and variance for the lag-k difference-based estimator and the second-order difference-based estimator in a finite sample size. Our approach can be extended to Tong`s estimator (2005) and be helpful to obtain optimal k.

LTE 시스템 채널 추정치의 후처리 기법 연구

유경렬(Kyung-Yul Yoo) 대한전기학회 2011 전기학회논문지 Vol.60 No.1

The Long Term Evolution (LTE) system is designed to provide a high quality data service for fast moving mobile users. It is based on the Orthogonal Frequency Division Multiplexing (OFDM) and relies its channel estimation on the training samples which are systematically built within the transmitting data. Either a preamble or a lattice type is used for the distribution of training samples and the latter suits better for the multipath fading channel environment whose channel frequency response (CFR) fluctuates rapidly with time. In the lattice-type structure, the estimation of the CFR makes use of the least squares estimate (LSE) for each pilot samples, followed by an interpolation both in timeand in frequency-domain to fill up the channel estimates for subcarriers corresponding to data samples. All interpolation schemes should rely on the pilot estimates only, and thus, their performances are bounded by the quality of pilot estimates. However, the additive noise give rise to high fluctuation on the pilot estimates, especially in a communication environment with low signal-to-noise ratio. These high fluctuations could be monitored in the alternating high values of the first forward differences (FFD) between pilot estimates. In this paper, we analyzed statistically those FFD values and propose a postprocessing algorithm to suppress high fluctuations in the noisy pilot estimates. The proposed method is based on a localized adaptive moving-average filtering. The performance of the proposed technique is verified on a multipath environment suggested on a 3GPP LTE specification. It is shown that the mean-squared error (MSE) between the actual CFR and pilot estimates could be reduced up to 68% from the noisy pilot estimates.

Speech Enhancement Based on Adaptive Noise Power Estimation Using Spectral Difference

CHOI, Jae-Hun,CHANG, Joon-Hyuk,KIM, Dong Kook,KIM, Suhyun The Institute of Electronics, Information and Comm 2011 IEICE transactions on fundamentals of electronics, Vol.ea94 No.10

<P>In this paper, we propose a spectral difference approach for noise power estimation in speech enhancement. The noise power estimate is given by recursively averaging past spectral power values using a smoothing parameter based on the current observation. The smoothing parameter in time and frequency is adjusted by the spectral difference between consecutive frames that can efficiently characterize noise variation. Specifically, we propose an effective technique based on a sigmoid-type function in order to adaptively determine the smoothing parameter based on the spectral difference. Compared to a conventional method, the proposed noise estimate is computationally efficient and able to effectively follow noise changes under various noise conditions.</P>

A Robust Estimator in Multivariate Regression Using Least Quartile Difference

Jung Kang-Mo The Korean Statistical Society 2005 Communications for statistical applications and me Vol.12 No.1

We propose an equivariant and robust estimator in multivariate regression model based on the least quartile difference (LQD) estimator in univariate regression. We call this estimator as the multivariate least quartile difference (MLQD) estimator. The MLQD estimator considers correlations among response variables and it can be shown that the proposed estimator has the appropriate equivariance properties defined in multivariate regressions. The MLQD estimator has high breakdown point as does the univariate LQD estimator. We develop an algorithm for MLQD estimate. Simulations are performed to compare the efficiencies of MLQD estimate with coordinatewise LQD estimate and the multivariate least trimmed squares estimate.

Effects of windowing filters in leak locating for buried water-filled cast iron pipes

이영섭 대한기계학회 2009 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.23 No.2

Arrival time difference or time delay estimation is critically important for detection of leak location in buried water supply pipes. Because the exact leak locating depends upon the precision of the arrival time difference estimation between leak signals measured by sensors and the propagation speed of the leak-related elastic wave, the research on the estimation of time delay has been one of the key issues in leak locating. The arrival time difference was estimated with the peak time of cross correlation functions of the measured signals. In this study six different window functions, including the basic rectangular, Roth, Wiener, SCOT, PHAT and maximum likelihood windows were applied. Experimental results against an actual buried pipe made of cast iron showed that the introduction of the window functions improved the precision of time delay estimation. In this paper, a new statistical approach, that combines all results of each window function, is suggested for better leak locating. Apart from the experiment, an intensive theoretical analysis in terms of signal processing is described.

First Order Difference-Based Error Variance Estimator in Nonparametric Regression with a Single Outlier

Park, Chun-Gun The Korean Statistical Society 2012 Communications for statistical applications and me Vol.19 No.3

We consider some statistical properties of the first order difference-based error variance estimator in nonparametric regression models with a single outlier. So far under an outlier(s) such difference-based estimators has been rarely discussed. We propose the first order difference-based estimator using the leave-one-out method to detect a single outlier and simulate the outlier detection in a nonparametric regression model with the single outlier. Moreover, the outlier detection works well. The results are promising even in nonparametric regression models with many outliers using some difference based estimators.

경제활동인구조사의 분산추정방법 검토

정구현,이주희,김능경 통계청 2008 통계연구 Vol.13 No.2

Economically Active Population Survey(EAPS) is rotation sampling which has been undertaken at some fixed rate every month since the beginning in 2005. One cycle(2005~2007) of rotation sampling was completed in 2007. The estimator of EAPS will be changed to reflect the effect of rotation sampling. Therefore we compare different variance estimation methods for EAPS. In this paper, the EAPS data of Dec. 2007 served as a sampling frame to create 500 simulated samples. The mean square error for the 500 sample estimates was compared to variance estimates obtained with Successive Difference Method, Linearization(Taylor Series) Method and Jackknife Method of variance estimation. We evaluate the different variance estimator for adequate variance estimation. 경제활동인구조사는 층화, 다단계 집락 및 사후층화 조정 등을 포함한 복합설계이다. 2005년부터 매월 일정규모의 표본을 교체하는 연동표본제를 실시하고 있으며 표본가구로 선정되면 3년간 계속해서 조사를 실시하는 반복조사이다. 연동표본 1주기(2005~2007년)가 마무리됨에 따라 연동표본의 영향을 반영한 추정식 개발과 동시에 분산추정식의 검토가 필요하다는 인식을 했다. 경제활동인구조사에 적합한 분산추정방법을 검토하기 위해 2007년 12월 자료를 이용하여 500개의 독립된 표본을 구축했다. 각 추정방법별로 계산된 분산을 비교하기 위해 MSE를 사용한다. 본 연구에서는 일반적으로 널리 쓰이는 분산추정방법을 살펴보고 모의실험을 통해 방법별 상대편향과 상대안정성을 고려하여 분산추정량을 평가하고자 한다.