• Title/Summary/Keyword: Time Estimator

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Robust spectral estimator from M-estimation point of view: application to the Korean housing price index (M-추정에 기반을 둔 로버스트 스펙트럴 추정량: 주택 가격 지수에 대한 응용)

  • Pak, Ro Jin
    • The Korean Journal of Applied Statistics
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    • v.29 no.3
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    • pp.463-470
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    • 2016
  • In analysing a time series on the frequency domain, the spectral estimator (or periodogram) is a very useful statistic to identify the periods of a time series. However, the spectral estimator is very sensitive in nature to outliers, so that the spectral estimator in terms of M-estimation has been studied by some researchers. Pak (2001) proposed an empirical method to choose a tuning parameter for the Huber's M-estimating function. In this article, we try to implement Pak's estimation proposal in the spectral estimator. We use the Korean housing price index as an example data set for comparing various M-estimating results.

Applications of an improved estimator of the constitutive relation error to plasticity problems

  • Gallimard, L.;Ladeveze, P.;Pelle, J.P.
    • Structural Engineering and Mechanics
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    • v.14 no.4
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    • pp.381-400
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    • 2002
  • This paper presents several applications of an improved estimator of the constitutive relation error (CRE) for plasticity problems. The cumulative aspect of the CRE estimator with respect to time is analyzed and we propose a first analysis of the local effectivity indexes of the CRE estimator in plasticity.

High Resolution Frequency Estimation of Real Sinusoids (고분해능의 주파수 추정 알고리즘 개발)

  • Seo, In-Yong
    • Proceedings of the KIEE Conference
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    • 2003.10a
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    • pp.279-282
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    • 2003
  • In this paper, we propose a new high resolution frequency estimator for real sinusoids by using short time data and the AWLS/MFT (Adaptive Weighted Least Squares/ Modulation Function Technique) algorithm. Monte-Carlo simulations verify better performances of the proposed frequency estimator and demonstrate that the proposed AWLS sinusoidal estimator is a high resolution estimator.

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Adaptive Microphone Array System with Self-Delay Estimator (지연 추정 기능을 갖는 적응 마이크로폰 어레이 알고리즘)

  • Jung Yang-Won;Kang Hong-Goo;Lee Chungyong;Youn Dae Hee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.1C
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    • pp.54-60
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    • 2005
  • In this Paper, an adaptive microphone array system with self-delay estimator is proposed. By showing that the adaptive blocking matrix (ABM) of the generalized sidelobe canceller (GSC) can estimate the relative time delay between each sensor, the proposed system utilizes the ABM not only for blocking target components in the blocked signal path, but also for estimating the relative time delay. Therefore, the proposed system requires only the GSC structure while maintaining the system performance similar to the conventional system using an additional time delay estimator as a preprocessor. Simulation results show that the performance of the proposed system is identical to the conventional system that uses an additional time delay estimation module.

Channel Estimation for OFDM Systems under Non-Sampled Space and Fast Time-Varying Channels (비 샘플 간격을 갖는 빠른 시변 채널 환경에서의 OFDM 시스템을 위한 채널 추정 기법)

  • 김동주;정성순;홍대식;강창언
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.2C
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    • pp.238-246
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    • 2004
  • In this paper, an estimator that take advantages of time and frequency correlation within an OFDM symbol is investigated. OFDM systems using the proposed estimator can be very effective in detecting signals under non-sampled space and time-varying channels. Also, under same complexity, the proposed estimator outperforms the previously proposed estimator. Since even if there are no assumption about channel correlation, the linear interpolation method instead of optimal interpolation using correct channel correlation is proposed in case the receiver does not know the channel correlation function in time domain. Therefore the proposed channel estimator help improving the performance of OFDM systems under non-sampled spaced and fast time-varying channels.

Multivariate analysis of longitudinal surveys for population median

  • Priyanka, Kumari;Mittal, Richa
    • Communications for Statistical Applications and Methods
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    • v.24 no.3
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    • pp.255-269
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    • 2017
  • This article explores the analysis of longitudinal surveys in which same units are investigated on several occasions. Multivariate exponential ratio type estimator has been proposed for the estimation of the finite population median at the current occasion in two occasion longitudinal surveys. Information on several additional auxiliary variables, which are stable over time and readily available on both the occasions, has been utilized. Properties of the proposed multivariate estimator, including the optimum replacement strategy, are presented. The proposed multivariate estimator is compared with the sample median estimator when there is no matching from a previous occasion and with the exponential ratio type estimator in successive sampling when information is available on only one additional auxiliary variable. The merits of the proposed estimator are justified by empirical interpretations and validated by a simulation study with the help of some natural populations.

Determination of Minimum Eigenvalue in a Continuous-time Weighted Least Squares Estimator (연속시간 하중최소자승 식별기의 최소고우치 결정)

  • Kim, Sung-Duck
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.9
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    • pp.1021-1030
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    • 1992
  • When using a least squares estimator with exponential forgetting factor to identify continuous-time deterministic system, the problem of determining minimum eigenvalue is described in this paper. It is well known fact that the convergence rate of parameter estimates relies on various factors consisting of the estimator and especially, theirproperties can be directly affected by all eigenvalues in the parameter error differential equation. Fortunately, there exists only one adjusting eigenvalue in the given estimator and then, the parameter convergence rates depend on this minimum eigenvalue. In this note, a new result to determine the minimum eigenvalue is proposed. Under the assumption that the input has as many spectral lines as the number of parameter estimates, it can be proven that the minimum eigenvalue converges to a constant value, which is a function of the forgetting factor and the parameter estimates number.

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Estimation of the Change Point in Monitoring the Mean of Autocorrelated Processes

  • Lee, Jae-Heon;Han, Jung-Hee;Jung, Sang-Hyun
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.155-167
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    • 2007
  • Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose the maximum likelihood estimator (MLE) for the process change point when a control chart is used in monitoring the mean of a process in which the observations can be modeled as an AR(1) process plus an additional random error. The performance of the proposed MLE is compared to the performance of the built-in estimator when they are used in EWMA charts based on the residuals. The results show that the proposed MLE provides good performance in terms of both accuracy and precision of the estimator.

l-STEP GENERALIZED COMPOSITE ESTIMATOR UNDER 3-WAY BALANCED ROTATION DESIGN

  • KIM K. W.;PARK Y. S.;KIM N. Y.
    • Journal of the Korean Statistical Society
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    • v.34 no.3
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    • pp.219-233
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    • 2005
  • The 3-way balanced multi-level rotation design has been discussed (Park Kim and Kim, 2003), where the 3-way balancing is done on interview time, in monthly sample and rotation group and recall time. A greater advantage of 3-way balanced design is accomplished by an estimator. To obtain the advantage, we generalized previous generalized composite estimator (GCE). We call this as l-step GCE. The variance of the l-step GCE's of various characteristics of interest are presented. Also, we provide the coefficients which minimize the variance of the l-step GCE. Minimizing a weighted sum of variances of all concerned estimators of interest, we drive one set of the compromise coefficient of l-step GCE's to preserve additivity of estimates.

Logistic Regression Method in Interval-Censored Data

  • Yun, Eun-Young;Kim, Jin-Mi;Ki, Choong-Rak
    • The Korean Journal of Applied Statistics
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    • v.24 no.5
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    • pp.871-881
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    • 2011
  • In this paper we propose a logistic regression method to estimate the survival function and the median survival time in interval-censored data. The proposed method is motivated by the data augmentation technique with no sacrifice in augmenting data. In addition, we develop a cross validation criterion to determine the size of data augmentation. We compare the proposed estimator with other existing methods such as the parametric method, the single point imputation method, and the nonparametric maximum likelihood estimator through extensive numerical studies to show that the proposed estimator performs better than others in the sense of the mean squared error. An illustrative example based on a real data set is given.