• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.385-399
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• 2003

We first introduce the quasi-score estimating function and applied the quasi-score estimating function to nonlinear time series models. We proposed the M quasi-score estimating functions bounded functions for the quasi-score estimating functions. Also, we investigated the asymptotic properties of quasi-likelihood estimators and M quasi-likelihood estimators. Simulation results show that the M quasi-likelihood estimators work better than the least squares estimators under the heavy-tailed distributions

• Communications for Statistical Applications and Methods
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• v.20 no.3
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• pp.185-191
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• 2013

Kiefer (1961) studied asymptotic behavior of empirical distribution using the law of the iterated logarithm. Robertson and Wright (1974a) discussed whether this type of result would hold for a maximum likelihood estimator of a stochastically ordered distribution function; however, we show that this cannot be achieved. We provide only a partial answer to this problem. The result is applicable to both estimation and testing problems under the restriction of stochastic ordering.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.273-284
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• 2004

Bayes estimation of parameters is considered for two independent exponential distributions with ordered means. Order restricted Bayes estimators for means are obtained with respect to inverted gamma, noninformative prior and uniform prior distributions, and their asymptotic properties are established. It is shown that the maximum likelihood estimator, restricted maximum likelihood estimator, unrestricted Bayes estimator, and restricted Bayes estimator of the mean are all consistent and have the same limiting distribution. These estimators are compared with the corresponding unrestricted Bayes estimators by Monte Carlo simulation.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.479-488
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• 2007

A sequential procedure is proposed in order to construct one-sided confidence intervals for a normal mean with guaranteed coverage probability and ${\beta}-protection$ when the normal mean and variance are identical. First-order asymptotic properties on the sequential sample size are found. The derived results hold with uniformity in the total parameter space or its subsets.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.349-356
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• 2010

The ordinary least squares based estimator of the disturbance variance in a regression model for spatial panel data is shown to be asymptotically unbiased and weakly consistent in the context of SAR(1), SMA(1) and SARMA(1,1)-disturbances when there is measurement error in the regressor matrix.

• 한국연소학회:학술대회논문집
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• 2014.11a
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• pp.135-137
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• 2014

Excess enthalpy flame propagating an porous inert medium, which recirculate exhaust heat to the upstream cold mixture, is theoretically analyzed. Using the activation-energy asymptotics, the flame structure is divided into the thin reaction and the gas-phase preheat zone, as is traditionally done. Ahead and behind of the two, there exist an outer preheat zone, where heat is convectively transferred from solid to gas, and a downstream re-equilibrium zone, where thermal equilibrium between phases is established. Asymptotic solutions of species and energy equations in each zone are obtained and then matched to each other, and finally the mass burning rate is obtained as a function of the flame propagation velocity with respect to the solid phase and physical properties of gas and solid.

• Journal of the Korean Mathematical Society
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• v.48 no.2
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• pp.431-447
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• 2011

We investigate the asymptotic behavior of positive solutions to the elliptic equation (0.1) ${\Delta}u+|x|^{l_1}u^p+|x|^{l_2}u^q=0$ in $\mathbb{R}^n$. We obtain a conclusion that, for n $\geq$ 3, -2 < $l_2$ < $l_1$ $\leq$ 0 and q > p > 1, any positive radial solution to (0.1) has the following properties: $lim_{r{\rightarrow}{\infty}}r^{\frac{2+l_1}{p-1}}\;u$ and $lim_{r{\rightarrow}0}r^{\frac{2+l_2}{q-1}}\;u$ always exist if $\frac{n+1_1}{n-2}$ < p < q, $p\;{\neq}\;\frac{n+2+2l_1}{n-2}$, $q\;{\neq}\;\frac{n+2+2l_2}{n-2}$. In addition, we prove that the singular positive solution of (0.1) is unique under some conditions.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.543-554
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• 1997

A family of some capability indices { $C_{p}$(.alpha.,.beta.); .alpha..geq.0, .beta..geq.0}, containing the indices $C_{p}$, $C_{{pk}}$, $C_{{pm}}$, and $C_{{pmk}}$, has been defined by Vannman(1993) for the case of two-sided specification interval. By varying the parameters of the family various capability indices with suitable properties are obtained. We derive tha asymptotic distribution of the family { $C_{p}$(.alpha.,.beta.); .alpha..geq.0,.beta..geq.0} under general proper conditions. It is also shown that the bootstrap approximation to the distribution of the estimator $C_{p}$(.alpha., .beta.) is vaild for almost all sample sequences. These asymptotic distributions would be used in constructing some bootstrap confidence intervals.tervals.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.57-76
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• 2007

Kriging is a nonparametric regression method used in geostatistics for estimating curves and surfaces for spatial data. It may come as a surprise that the Kriging estimator, normally derived as the best linear unbiased estimator, is also the solution of a particular variational problem. Thus, Kriging estimators can also be interpreted as generalized smoothing splines where the roughness penalty is determined by the covariance function of a spatial process. We build off the early work by Silverman (1982, 1984) and the analysis by Cox (1983, 1984), Messer (1991), Messer and Goldstein (1993) and others and develop an equivalent kernel interpretation of geostatistical estimators. Given this connection we show how a given covariance function influences the bias and variance of the Kriging estimate as well as the mean squared prediction error. Some specific asymptotic results are given in one dimension for Matern covariances that have as their limit cubic smoothing splines.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.10
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• pp.848-855
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• 1989

The asymptotic properties of the Overdetermined Yule-Walker (OYW) estimators were studied. A formula was derived for the asymptotic covariance matrix of the estimation errors. It verified the experimentally observed fact that the frequency estimation accuracy is generally improved as the number of Yule-Walker equations is increased. The asymptotic estimation accuracies of the OYW method were compared with the Cramer-Rao low bound.