• Title/Summary/Keyword: Variance estimation

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Modelling of a pH titration process and design of a self-tuning pH controller (pH 적정공정의 모델링 및 자기동조 제어기 설계)

  • 김우태;이혁희;최태호;이지태
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.476-481
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    • 1988
  • In this paper a pH process of a weak acid with a strong base is modeled into a bilinear form, and a self-tuning pH control algorithm which is robust against initial values of solution and disturbances is presented. The control algorithm employs the recursive least square method for the parameter estimation and the generalised minimum variance criterion as the objective function. The computer simulation shows that the tracking of desired pH values is obtained in satisfactory manner regardless of the initial values chosen for the process.

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A NOTE ON THE BIVARIATE PARETO DISTRIBUTION

  • Cho, Bong Sik;Jung, Sun Young
    • Honam Mathematical Journal
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    • v.35 no.1
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    • pp.29-35
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    • 2013
  • The Fisher information matrix plays a significant role i statistical inference in connection with estimation and properties of variance of estimators. Using Bivariate Lomax distribution, we can define "statistical model" and drive the Fisher information matrix of Bivariate Lomax distribution. In this paper, we correct the wrong of the paper [7].

Optimal estimation of rock joint characteristics using simulated annealing technique - A case study

  • Hong, Chang-Woo;Jeon, Seok-Won
    • 한국지구물리탐사학회:학술대회논문집
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    • 2003.11a
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    • pp.78-82
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    • 2003
  • In this paper, simulated annealing technique was used to estimate the rock joint characteristics, RMR(rock mass rating) values, to overcome the defects of ordinary kriging. Ordinary kriging reduced the variance of data, so lost the characteristics of distribution. Simulated annealing technique could reflect the distribution feature and the spatial correlation of the original data. Through the comparisons between three times simulations, the uncertainty of the simulation could be quantified, and sufficient results were obtained.

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Design of the optimal stochastic inputs for linear system parameter estimation (선형계통의 파라미터 추정을 위한 최적 확률 입력신호의 설계)

  • ;;Lee, S. W.
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10b
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    • pp.168-173
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    • 1987
  • The optimal Input design problem for linear system Which have the common parameters in the system and noise transfer functions. Exploiting the assumed Model structure and deriving the information matrix structure in detail, D-optimal open-loop stochastic input can be realized as an ARMA process under the Input or output variance constraints. In spite of the reduced order, It Is necessary to develop an efficient algorithms for the optimation with respect to the .rho..

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Implementation of SSB/BPSK-DS/CDMA Baseband Modem (SSB/BPSK-DS/CDMA Baseband 모뎀 설계 및 구현)

  • 노시창;임명섭
    • Proceedings of the IEEK Conference
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    • 2001.06a
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    • pp.5-8
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    • 2001
  • SSB(Single Sideband) modulation scheme is high bandwidth efficient method in the mobile communication system compared with present DSB(Double Sideband) modulation scheme. Using the othogonality between inphase PN code and Hilbert transformed quadrature PN code, we propose phase estimation structure that enables coherent demodulation in the reverse link basestation receiver Several system characteristics, bit error rate and phase error variance, are simulated and compared with balanced QPSK DS/CDMA system. To verify system performance, SSB/BPSK-DS/CDMA test board is implemented using FPGA chips.

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Some Computational Contribution on the Estimation Procedure of a First Order Moving Average

  • Kim, Dai-Young
    • Journal of the Korean Statistical Society
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    • v.2 no.1
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    • pp.9-15
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    • 1973
  • In the first-order moving average model, we present the exact likelihood equations as function of variance, correlation and parameters of coefficients in the orthogonally transformed model. Existence of maximum likelihood estimates for these unknowns are studied and a computational method is provided. (Because of the limited space Ive do not present the computer program which is written in FORTRAN.) 40 sets of generated data and economic data are used to demonstrate, and few of them are presented in the Appendix. A numerical comparison of MLE with the efficient estimate proposed by Durbin is presented in the particular case.

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Estimation of Overflow Probabilities in Parallel Networks with Coupled Inputs

  • Lee, Jiyeon;Kweon, Min Hee
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.257-269
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    • 2001
  • The simulation is used to estimate an overflow probability in a stable parallel network with coupled inputs. Since the general simulation needs extremely many trials to obtain such a small probability, the fast simulation is proposed to reduce trials instead. By using the Cramer’s theorem, we first obtain an optimally changed measure under which the variance of the estimator is minimized. Then, we use it to derive an importance sampling estimator of the overflow probability which enables us to perform the fast simulation.

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Non-negative Unbiased MSE Estimation under Stratified Multi-stage Sampling

  • Kim, Kyuseong
    • Journal of the Korean Statistical Society
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    • v.30 no.4
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    • pp.637-644
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    • 2001
  • We investigated two kinds of mean square error (MSE) estimator of homogeneous linear estimator (HLE) for the population total under stratified multi-stage sampling. One is studied when the second stage variance component is estimable and the other is found in cafe it is not estimable. The proposed estimators are necessary forms of non-negative unbiased MSE estimators of HLE.

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Limiting Distributions of Trimmed Least Squares Estimators in Unstable AR(1) Models

  • Lee, Sangyeol
    • Journal of the Korean Statistical Society
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    • v.28 no.2
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    • pp.151-165
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    • 1999
  • This paper considers the trimmed least squares estimator of the autoregression parameter in the unstable AR(1) model: X\ulcorner=ØX\ulcorner+$\varepsilon$\ulcorner, where $\varepsilon$\ulcorner are iid random variables with mean 0 and variance $\sigma$$^2$> 0, and Ø is the real number with │Ø│=1. The trimmed least squares estimator for Ø is defined in analogy of that of Welsh(1987). The limiting distribution of the trimmed least squares estimator is derived under certain regularity conditions.

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Nonparametric Estimation using Regression Quantiles in a Regression Model

  • Han, Sang-Moon;Jung, Byoung-Cheol
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.793-802
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    • 2012
  • One proposal is made to construct a nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of the idea of minimizing approximate variance of a proposed estimator using regression quantiles. This nonparametric estimator and some other L-estimators are studied and compared with well known M-estimators through a simulation study.