• Title/Summary/Keyword: 근사계수

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자기회귀계수에 대한 소표본 점근추론

  • Na, Jong-Hwa;Kim, Jeong-Suk;Jang, Yeong-Mi
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.05a
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    • pp.209-213
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    • 2005
  • 본 논문에서는 1차 자기회귀모형에서 자기회귀계수에 대한 여러 가지 추정량들의 분포함수에 대한 근사적추론 방법에 대해 연구하였다. 이차형식에 대한 안장점근사의 결과를 이용한 이 근사법은 여러 형태의 추정량들에 대해 근사분포의 유도과정이 불필요하며, 소표본은 물론 통계적 추론의 주요 관심영역에서의 근사정도가 매우 뛰어난 장점을 가지고 있다. 모의실험을 통해 Edgeworth근사를 비롯한 기존의 여러 근사법보다 효율이 뛰어남을 확인하였다.

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Small Sample Asymptotic Inferences for Autoregressive Coefficients via Saddlepoint Approximation (안장점근사를 이용한 자기회귀계수에 대한 소표본 점근추론)

  • Na, Jong-Hwa;Kim, Jeong-Sook
    • The Korean Journal of Applied Statistics
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    • v.20 no.1
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    • pp.103-115
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    • 2007
  • In this paper we studied the small sample asymptotic inference for the autoregressive coefficient in AR(1) model. Based on saddlepoint approximations to the distribution of quadratic forms, we suggest a new approximation to the distribution of the estimators of the noncircular autoregressive coefficients. Simulation results show that the suggested methods are very accurate even in the small sample sizes and extreme tail area.

A Study on Noise Reduction Method using Wavelet Approximation Coefficient-based Distribution Characteristics (웨이브렛 근사계수 기반의 분포특성을 이용한 잡음 제거 방법에 관한 연구)

  • Bae, Sang-Bum;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.2
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    • pp.513-520
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    • 2010
  • The degradation phenomenon caused by noises significantly corrupts digitalized data. Therefore, a variety of methods to preserve the edge component of signals and remove noise simultaneously have been used in time domain and frequency domain. In this paper, we have proposed a new noise reduction algorithm using wavelet approximation coefficients to reduce the mixed noise overlapping the signal. The proposed algorithm adopts the distribution characteristics of the error function which is obtained by accumulating the wavelet approximation coefficients, in order to improve the capability to separate edges of the signal and noises.

Reverberation Characterization and Suppression by Means of Low Rank Approximation (낮은 계수 근사법을 이용한 표준 잔향음 신호 획득 및 제거 기법)

  • 윤관섭;최지웅;나정열
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.5
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    • pp.494-502
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    • 2002
  • In this paper, the Low Rank Approximation (LRA) method to suppress the interference of signals from temporal fluctuations is applied. The reverberation signals and temporally fluctuating signals are separated from the measured data using the Ink. The Singular value decomposition (SVD) method is applied to extract the low rank and the temporally stable reverberation was extracted using the LRA. The reverberation suppression is performed on the LRA residual value obtained by removing the approximate reverberation signals. In overall, the method can be applied to the suppression of reververation in active sonar system as well as to the modeling of reverberation.

Derivation of Coherent Reflection Coefficient at Mid and Low Frequency for a Rough Surface (불규칙 경계면에 대한 중저주파수 간섭 반사 계수 유도)

  • Chu, Young-Min;Seong, Woo-Jae;Byun, Sung-Hoon;Kim, Sea-Moon
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.3
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    • pp.174-186
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    • 2009
  • When we apply a propagation model to the ocean with boundaries, we can calculate reflected wave using reflection coefficient suggested by Rayleigh assuming the boundaries are flat. But boundaries in ocean such as sea surface and sea bottom have an irregular rough surface. To calculate the reflection loss for an irregular boundary, it is needed to compute the coherent reflection coefficient based on an experimental formula or scattering theory. In this article, we derive the coherent reflection coefficients for a fluid-fluid interface using perturbation theory, Kirchhoff approximation and small-slope approximation respectively. Based on each formula, we can calculate coherent reflection coefficients for a rough sea surface or sea bottom, and then compare them to the Rayleigh reflection coefficient to analyze the reflection loss for a random rough surface. In general, the coherent reflection coefficient based on small-slope approximation has a wide valid region. Comparing it with the coherent reflection coefficients derived from the Kirchhoff approximation and perturbation theory, we discuss a valid region of them.

Distribution Approximation of the Two Dimensional Discrete Cosine Transform Coefficients of Image (영상신호 2차원 코사인 변환계수의 분포근사화)

  • 심영석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.10 no.3
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    • pp.130-134
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    • 1985
  • In two-dimensional discrete cosine transform(DCT) coding, the measurements of the distributions of the transform coefficients are important because a better approximation yields a smaller mean square distorition. This paper presents the results of distribution tests which indicate that the statistics of the AC coefficients are well approximated to a generalized Gaussian distribution whose shape parameter is 0.6. Furthermore, from a simulation of the DCT coding, it was shown that the above approximation yields a higher experimental SNR and a better agreement between theory and simulation than the Gaussian or Laplacian assumptions.

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Approximate Variance of Least Square Estimators for Regression Coefficient under Inclusion Probability Proportional to Size Sampling (포함확률비례추출에서 회귀계수 최소제곱추정량의 근사분산)

  • Kim, Kyu-Seong
    • Communications for Statistical Applications and Methods
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    • v.19 no.1
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    • pp.23-32
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    • 2012
  • This paper deals with the bias and variance of regression coefficient estimators in a finite population. We derive approximate formulas for the bias, variance and mean square error of two estimators when we select a fixed-size inclusion probability proportional to the size sample and then estimate regression coefficients by the ordinary least square estimator as well as the weighted least square estimator based on the selected sample data. Necessary and sufficient conditions for the comparison of the two estimators in terms of variance and mean square error are suggested. In addition, a simple example is introduced to numerically compare the variance and mean square error of the two estimators.

Analysis of Series Arc Fault Current Using Discrete Wavelet Transform (이산 웨이블렛 변환을 이용한 직렬 아크고장전류 분석)

  • Bang, Sun-Bae;Kim, Chong-Min;Park, Chong-Yeun
    • Proceedings of the KIEE Conference
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    • 2009.04a
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    • pp.318-321
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    • 2009
  • 누전차단기 설치 상태에서도 전기화재가 지속적으로 발생함에 따라 전기화재의 원인이 되는 전기 아크에 대한 관심이 증가하고 있는 실정으로 본 논문에서는 UL1699의 아크 저해시험(inhibition tests)에서 제시하고 있는 직렬 아크코장시험(Arc generator test)을 실시하고, 아크고장전류 분석방법으로 최근에 많이 사용되고 있는 이산 웨이블렛 변환을 이용한 3가지 분석방법에 대하여 아크고장전류 검출 확률을 분석하였다. 분석결과, (1) 근사계수 분석에 의한 최대치 변화율 실효치 변화율 분석방법은 46%의 검출 확률을 얻을 수 있었고, (2) 상세계수 분석에 의한 최대치 변화율 실효치 변화율 분석방법은 62%, (3) 근사계수 분석에 의한 잡음량 변화율 shoulder 변화율 분석방법은 100% 검출 확률을 얻을 수 있었다.

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A comparative study on the confidence intervals for regression coefficients in a panel regression model (패널회귀모형에서 회귀계수의 신뢰구간에 관한 비교연구)

  • 송석헌;전명식;정병철
    • The Korean Journal of Applied Statistics
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    • v.12 no.2
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    • pp.449-461
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    • 1999
  • 본 논문에서는 패널회귀모형에서 내부변환(within transformation) 추정량을 이용하여 회귀계수에 대한 정확한 신뢰구간을 제시하였다. 아울러 이러한 신뢰구간의 효율성을 신뢰계수(confidence coefficient)와 신뢰구간의 평균길이(average length of confidence interval)을 사용하여 모의실험을 통하여 다른 근사적 신뢰구간들과 비교하였다. 실험결과, 내부변환추정량을 이용한 신뢰구간은 다른 근사적 신뢰구간들에 비해 명목신뢰계수를 정확히 유지하였고, 신뢰구간의 평균길이도 다른 방법들에 비해 짧은 결과를 보았다.

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Design-based Properties of Least Square Estimators in Panel Regression Model (패널회귀모형에서 회귀계수 추정량의 설계기반 성질)

  • Kim, Kyu-Seong
    • Survey Research
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    • v.12 no.3
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    • pp.49-62
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    • 2011
  • In this paper we investigate design-based properties of both the ordinary least square estimator and the weighted least square estimator for regression coefficients in panel regression model. We derive formulas of approximate bias, variance and mean square error for the ordinary least square estimator and approximate variance for the weighted least square estimator after linearization of least square estimators. Also we compare their magnitudes each other numerically through a simulation study. We consider a three years data of Korean Welfare Panel Study as a finite population and take household income as a dependent variable and choose 7 exploratory variables related household as independent variables in panel regression model. Then we calculate approximate bias, variance, mean square error for the ordinary least square estimator and approximate variance for the weighted least square estimator based on several sample sizes from 50 to 1,000 by 50. Through the simulation study we found some tendencies as follows. First, the mean square error of the ordinary least square estimator is getting larger than the variance of the weighted least square estimator as sample sizes increase. Next, the magnitude of mean square error of the ordinary least square estimator is depending on the magnitude of the bias of the estimator, which is large when the bias is large. Finally, with regard to approximate variance, variances of the ordinary least square estimator are smaller than those of the weighted least square estimator in many cases in the simulation.

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