• 제목/요약/키워드: Maximum likelihood estimate

검색결과 374건 처리시간 0.025초

변화시점이 있는 영과잉-포아송모형에서 돌출대립가설에 대한 우도비검정 (Likelihood Ratio Test for the Epidemic Alternatives on the Zero-Inflated Poisson Model)

  • 김경무
    • Journal of the Korean Data and Information Science Society
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    • 제9권2호
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    • pp.247-253
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    • 1998
  • 영과잉-포아송모형에서 변화시점이 있는 경우, 돌출대립가설에 대한 우도비검정을 이용하여 변화시점의 유 무를 알아보았다. 변화시점에 대한 추정은 최소제곱법을 이용하였고 이를 최우추정법을 이용하기 위한 초기치로 활용하였다. 또한 대립가설에 대한 몇가지 흥미있는 모수들을 적률법을 이용하여 추정하였다. 모의실험을 통하여 이들 추정 량을 비교하였고 결과 변화시점에 대한 추정은 최소제곱법보다는 최우추정법이 바람직하게 나타났고 흥미있는 몇가지 모수들에 대해서는 최우추정량이 적률추정량보다 우수하게 나타났다.

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Biased SNR Estimation using Pilot and Data Symbols in BPSK and QPSK Systems

  • Park, Chee-Hyun;Hong, Kwang-Seok;Nam, Sang-Won;Chang, Joon-Hyuk
    • Journal of Communications and Networks
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    • 제16권6호
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    • pp.583-591
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    • 2014
  • In wireless communications, knowledge of the signal-to-noise ratio is required in diverse communication applications. In this paper, we derive the variance of the maximum likelihood estimator in the data-aided and non-data-aided schemes for determining the optimal shrinkage factor. The shrinkage factor is usually the constant that is multiplied by the unbiased estimate and it increases the bias slightly while considerably decreasing the variance so that the overall mean squared error decreases. The closed-form biased estimators for binary-phase-shift-keying and quadrature phase-shift-keying systems are then obtained. Simulation results show that the mean squared error of the proposed method is lower than that of the maximum likelihood method for low and moderate signal-to-noise ratio conditions.

단발 터어보프롭 항공기 동적 모델의 파라메터추정 (Parameter estimation of a single turbo-prop aircraft dynamic model)

  • 이환;이상기
    • 제어로봇시스템학회논문지
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    • 제4권1호
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    • pp.38-44
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    • 1998
  • The modified maximum likelihood estimation method is used to estimate the nondimensional aerodynamic derivatives of a single turbo-prop aircraft at a specified flight condition for the best deduction of the dynamic characteristics. In wind axes the six degree of freedom equations are algebraically linearized so that the linear state equation contains aerodynamic derivatives in a state-space form and is used in the maximum likelihood method. The simulated data added with the measurement noise is used as a flight test data which is necessary to the estimation of nondimensional aerodynamic derivatives. It is obtained by implementing the 6-DOF nonlinear flight simulation. In the flight simulation, the effects of several control input types, control deflection amplitudes, and the turbulence intensities on the statistical convergence criteria are also examined and quantitative analysis of the results is discussed.

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Bayesian Inference for Censored Panel Regression Model

  • Lee, Seung-Chun;Choi, Byongsu
    • Communications for Statistical Applications and Methods
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    • 제21권2호
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    • pp.193-200
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    • 2014
  • It was recognized by some researchers that the disturbance variance in a censored regression model is frequently underestimated by the maximum likelihood method. This underestimation has implications for the estimation of marginal effects and asymptotic standard errors. For instance, the actual coverage probability of the confidence interval based on a maximum likelihood estimate can be significantly smaller than the nominal confidence level; consequently, a Bayesian estimation is considered to overcome this difficulty. The behaviors of the maximum likelihood and Bayesian estimators of disturbance variance are examined in a fixed effects panel regression model with a limited dependent variable, which is known to have the incidental parameter problem. Behavior under random effect assumption is also investigated.

Wakeby Distribution and the Maximum Likelihood Estimation Algorithm in Which Probability Density Function Is Not Explicitly Expressed

  • Park Jeong-Soo
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.443-451
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    • 2005
  • The studied in this paper is a new algorithm for searching the maximum likelihood estimate(MLE) in which probability density function is not explicitly expressed. Newton-Raphson's root-finding routine and a nonlinear numerical optimization algorithm with constraint (so-called feasible sequential quadratic programming) are used. This algorithm is applied to the Wakeby distribution which is importantly used in hydrology and water resource research for analysis of extreme rainfall. The performance comparison between maximum likelihood estimates and method of L-moment estimates (L-ME) is studied by Monte-carlo simulation. The recommended methods are L-ME for up to 300 observations and MLE for over the sample size, respectively. Methods for speeding up the algorithm and for computing variances of estimates are discussed.

Generalized nonlinear percentile regression using asymmetric maximum likelihood estimation

  • Lee, Juhee;Kim, Young Min
    • Communications for Statistical Applications and Methods
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    • 제28권6호
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    • pp.627-641
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    • 2021
  • An asymmetric least squares estimation method has been employed to estimate linear models for percentile regression. An asymmetric maximum likelihood estimation (AMLE) has been developed for the estimation of Poisson percentile linear models. In this study, we propose generalized nonlinear percentile regression using the AMLE, and the use of the parametric bootstrap method to obtain confidence intervals for the estimates of parameters of interest and smoothing functions of estimates. We consider three conditional distributions of response variables given covariates such as normal, exponential, and Poisson for three mean functions with one linear and two nonlinear models in the simulation studies. The proposed method provides reasonable estimates and confidence interval estimates of parameters, and comparable Monte Carlo asymptotic performance along with the sample size and quantiles. We illustrate applications of the proposed method using real-life data from chemical and radiation epidemiological studies.

Estimation of Random Coefficient AR(1) Model for Panel Data

  • Son, Young-Sook
    • Journal of the Korean Statistical Society
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    • 제25권4호
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    • pp.529-544
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    • 1996
  • This paper deals with the problem of estimating the autoregressive random coefficient of a first-order random coefficient autoregressive time series model applied to panel data of time series. The autoregressive random coefficients across individual units are assumed to be a random sample from a truncated normal distribution with the space (-1, 1) for stationarity. The estimates of random coefficients are obtained by an empirical Bayes procedure using the estimates of model parameters. Also, a Monte Carlo study is conducted to support the estimation procedure proposed in this paper. Finally, we apply our results to the economic panel data in Liu and Tiao(1980).

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A Mathematical model to estimate the wind power using three parameter Weibull distribution

  • Seshaiah, C.V.;Sukkiramathi, K.
    • Wind and Structures
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    • 제22권4호
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    • pp.393-408
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    • 2016
  • Weibull distribution is a suitable distribution to use in modeling the life time data. It has been found to be a exact fit for the empirical distribution of the wind speed measurement samples. In brief this paper consist of important properties and characters of Weibull distribution. Also we discuss the application of Weibull distribution to wind speed measurements and derive an expression for the probability distribution of the power produced by a wind turbine at a fixed location, so that the modeling problem reduces to collecting data to estimate the three parameters of the Weibull distribution using Maximum likelihood Method.

Estimation of Genetic and Phenotypic Covariance Functions for Body Weight as Longitudinal Data of SD-II Swine Line

  • Liu, Wenzhong;Cao, Guoqing;Zhou, Zhongxiao;Zhang, Guixian
    • Asian-Australasian Journal of Animal Sciences
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    • 제15권5호
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    • pp.622-626
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    • 2002
  • Growth records over six generations of 686 pigs in SD-II Swine Line were used to estimate the genetic and phenotypic covariance functions for body weight as longitudinal data. A random regression model with Legendre polynomials of age as independent variables was used to estimate the (co)variances among the regression coefficients, thus the coefficients of genetic and permanent environmental covariance functions by restricted maximum likelihood employing the average information algorithm. The results showed that, using litter effect as additional random effect, a reduced order of fit did not describe the data adequately. For all five orders of fit, however, the change trends of genetic and phenotypic (co)variances were very similar from ${\kappa}$=3 onwards.

와이블 모형의 모수 추정에서 분할법의 효율성 (Piecewise Weibull Model with Covariates)

  • 정대현;김주성;원동유
    • Journal of the Korean Data and Information Science Society
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    • 제11권2호
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    • pp.295-302
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    • 2000
  • 생존분석에서 널리 이용되고 있는 모형 중 하나인 와이블 모형에 대해 효율적인 모수 추정에 대해 연구하였다. 공변량을 포함하고 있는 와이블 모형의 모수를 추정하기 위하여 전 치료기간을 여러 단계로 나누어 최대우도법을 적용하는 분할법을 소개하였다. 실제의 자료를 적용하여 분할법과 비분할법으로 모수를 추정하여 비교한 결과 분할법의 효율성을 입증하였다.

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