• Title/Summary/Keyword: Unbiasedness

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Unbiasedness or Statistical Efficiency: Comparison between One-stage Tobit of MLE and Two-step Tobit of OLS

  • Park, Sun-Young
    • International Journal of Human Ecology
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    • v.4 no.2
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    • pp.77-87
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    • 2003
  • This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

Asymptotic Consistency of Least Squares Estimators in Fuzzy Regression Model

  • Yoon, Jin-Hee;Kim, Hae-Kyung;Choi, Seung-Hoe
    • Communications for Statistical Applications and Methods
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    • v.15 no.6
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    • pp.799-813
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    • 2008
  • This paper deals with the properties of the fuzzy least squares estimators for fuzzy linear regression model. Especially fuzzy triangular input-output model including error term is proposed. The error term is considered as a fuzzy random variable. The asymptotic unbiasedness and the consistency of the estimators are proved using a suitable metric.

A Note on the Asymptotic Property of S2 in Linear Regression Model with Correlated Errors

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.233-237
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    • 2003
  • An asymptotic property of the ordinary least squares estimator of the disturbance variance is considered in the regression model with correlated errors. It is shown that the convergence in probability of S$^2$ is equivalent to the asymptotic unbiasedness. Beyond the assumption on the design matrix or the variance-covariance matrix of disturbances error, the result is quite general and simplify the earlier results.

A Finite Memory Structure Smoothing Filter and Its Equivalent Relationship with Existing Filters (유한기억구조 스무딩 필터와 기존 필터와의 등가 관계)

  • Kim, Min Hui;Kim, Pyung Soo
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.2
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    • pp.53-58
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    • 2021
  • In this paper, an alternative finite memory structure(FMS) smoothing filter is developed for discrete-time state-space model with a control input. To obtain the FMS smoothing filter, unbiasedness will be required beforehand in addition to a performance criteria of minimum variance. The FMS smoothing filter is obtained by directly solving an optimization problem with the unbiasedness constraint using only finite measurements and inputs on the most recent window. The proposed FMS smoothing filter is shown to have intrinsic good properties such as deadbeat and time-invariance. In addition, the proposed FMS smoothing filter is shown to be equivalent to existing FMS filters according to the delay length between the measurement and the availability of its estimate. Finally, to verify intrinsic robustness of the proposed FMS smoothing filter, computer simulations are performed for a temporary model uncertainty. Simulation results show that the proposed FMS smoothing filter can be better than the standard FMS filter and Kalman filter.

Receding Horizon Finite Memory Controls for Output Feedback Controls of Discrete-Time State Space Models

  • Han, Soo-Hee;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1896-1900
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    • 2003
  • In this paper, a new type of output feedback control, called a receding horizon finite memory control (RHFMC), is proposed for stochastic discrete-time state space systems. Constraints such as linearity and finite memory structure with respect to an input and an output, and unbiasedness from the optimal state feedback control are required in advance. The proposed RHFMC is chosen to minimize an optimal criterion with these constraints. The RHFMC is obtained in an explicit closed form using the output and input information on the recent time interval. It is shown that the RHFMC consists of a receding horizon control and an FIR filter. The stability of the RHFMC is investigated for stochastic systems.

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Minimum Variance FIR Smoother for Model-based Signals

  • Kwon, Bo-Kyu;Kwon, Wook-Hyun;Han, Soo-Hee
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2516-2520
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    • 2005
  • In this paper, finite impulse response (FIR) smoothers are proposed for discrete-time systems. The proposed FIR smoother is designed under the constraints of linearity, unbiasedness, FIR structure, and independence of the initial state information. It is also obtained by directly minimizing the performance criterion with unbiased constraints. The approach to the MVF smoother proposed in this paper is logical and systematic, while existing results have heuristic assumption, such as infinite covariance of the initial state. Additionally, the proposed MVF smoother is based on the general system model that may have the singular system matrix and has both system and measurement noises. Thorough simulation studies, it is shown that the proposed MVF smoother is more robust against modeling uncertainties numerical errors than fixed-lag Kalman smoother which is infinite impulse response (IIR) type estimator.

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Assessment of Properties of Error Terms in Design of Experiment (실험계획법에서 오차항의 가정 검토방안)

  • Choe, Seong-Un
    • Proceedings of the Safety Management and Science Conference
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    • 2012.04a
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    • pp.579-583
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    • 2012
  • The Design of Experiment (DOE) is a most practical technique when establishing an optimal condition for production technology in Six Sigma innovation project. This research proposes the assessment of properties of error terms, such as normality, equal variance, unbiasedness and independence. The properties of six nonparametric ranking techniques for checking normality assumption are discussed as well as run test which is used to identify the randomness, and to check unbiased assumption. Furthermore, Durbin-Watson (DW) statistics and ARIMA (p,d,q) process are discussed to identify the serial correlation.

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An Empirical Study on Asia Foreign Exchange Market Efficiency (아시아 외환시장의 효율성 분석)

  • 장맹렬;송봉윤
    • Journal of Korea Port Economic Association
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    • v.19 no.2
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    • pp.111-139
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    • 2003
  • In this paper, the unbiasedness hypothesis cannot be rejected for JPY. It means that Japanese forward exchange market is efficient. This implies that there would not be an unusual profit from speculation. However, the unbiasedness hypothesis can be rejected for THB, HKD, IDR. It means that Asian forward exchange market is inefficient. This implies that there would be an unusual profit from all available information. This suggests that forward exchange rates cannot be an unbiased estimator of future spot exchange rate. This result explains that the actual pricing for forward rate is not based on the international financial market's pricing mechanism of interest rate parity theory, but rather depends upon that simple market expectations and aspirations.

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Representative of Sample and Efficiency of Estimation (표본의 대표성과 추정의 효율성)

  • Kim, Kyu-Seong
    • Survey Research
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    • v.6 no.1
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    • pp.39-62
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    • 2005
  • In this paper we investigate some concepts frequently called in sample surveys such as 'representative of sample' as well as 'consistency', 'unbiasedness', and 'efficiency' in estimation. The first is strongly related with sampling procedure including coverage rate of survey population, response rate in establishment survey, and recruit rate of final samples. The others, however, are concerned with both sampling design and corresponding estimators simultaneously. Whereas both consistency and unbiasedness are based on the representative sample, efficiency does not depend on the representative sample. The representative of sample can be increased by raising the rate of coverage, response and recruit as well. Consistency may be investigated according to variables of interest and auxiliary variables. The well-known raing-ratio weighting method is a method to increase consistency of auxiliary variables by means of matching population size in each cell. Efficiency is not directly related with the representative of sample, and allocation methods such as proportional and Neyman allocation in stratified sampling and post-stratification are all methods to increase the efficiency of estimation under the condition of satisfying the representative of sample.

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