• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 춘계 학술발표회 논문집
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• pp.95-100
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• 2005

In this paper a class of multifactor designs for estimating the slope of second order response surface regression models with correlated errors is considered. General conditions for second order slope rotatability over all directions and also with respect to the maximum directional variance in case of k=2 have been derived assuming errors have a general correlated error structure. And we consider the measures for evaluating slope rotatability with correlated errors similar to in case of uncorrelated error structures.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.513-518
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• 1987

In this paper the error equations of the SDINS aligned by the gyrocompass are derived considering that the alignment errors are correlated to the sensor errors. Also the navigation errors due to the correlated errors are simulated by this error equations. The simulations are performed by the covariance analysis method, assumed all the sensor errors are random constants. The simulation results show that while the INS maintains the alignment attitude the cancellation takes place between the correlated errors, but once the INS changes attitude this cancellation effect is perturbed.

• 품질경영학회지
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• 제16권2호
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• pp.68-81
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• 1988

Testing procedures for a detection of change point in the regression model with correlated errors are discussed. A Bayesian approach is adopted and applied to a regression model with errors following an AR(1) model.

• Communications for Statistical Applications and Methods
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• 제28권6호
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• pp.595-610
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• 2021

Recently a few articles have derived robust first-order rotatable and D-optimal designs for the lifetime response having distributions gamma, lognormal, Weibull, exponential assuming errors that are correlated with different correlation structures such as autocorrelated, intra-class, inter-class, tri-diagonal, compound symmetry. Practically, a first-order model is an adequate approximation to the true surface in a small region of the explanatory variables. A second-order model is always appropriate for an unknown region, or if there is any curvature in the system. The current article aims to extend the ideas of these articles for second-order models. Invariant (free of the above four distributions) robust (free of correlation parameter values) second-order rotatable designs have been derived for the intra-class and inter-class correlated error structures. Second-order rotatability conditions have been derived herein assuming the response follows non-normal distribution (any one of the above four distributions) and errors have a general correlated error structure. These conditions are further simplified under intra-class and inter-class correlated error structures, and second-order rotatable designs are developed under these two structures for the response having anyone of the above four distributions. It is derived herein that robust second-order rotatable designs depend on the respective error variance covariance structure but they are independent of the correlation parameter values, as well as the considered four response lifetime distributions.

• Journal of applied mathematics & informatics
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• 제16권1_2호
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• pp.143-150
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• 2004

In this paper we study the estimation problem of individual weights of objects using an A-optimal chemical balance weighing design. We assume that in this model errors are correlated and they have the same variances. The lower bound of tr$(X'G^{-1}X)^{-1}$ is obtained and a necessary and sufficient condition for this lower bound to be attained is given. There is given new construction method of A-optimal chemical balance weighing design.

• Communications for Statistical Applications and Methods
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• 제10권1호
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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.

• Preventive Nutrition and Food Science
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• 제7권3호
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• pp.265-272
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• 2002

In this study, we examined the effects of dietary fatty acids on the fatty acid composition of phospholipid fractions in regions of the brain and on behavioral development in rats. The Sprague Dawley rats were fed the experimental diets 3~4 wks prior to the conception. Experimental diets consisted of 10% fat(wt/wt) which were from either safflower oil (SO, poor in $\omega$3 fatty acids), mixed oil MO, P/M/S ratio : 1:1.4:1, $\omega$6/$\omega$3 ratio = 6.3), or mixed oil supplemented with vitamin E (+500 mg/kg diet). At 3 and 9 weeks of age, frontal cortex (FC), corpus striatum (CS), hippocampus (H), and cerebellum (CB) were dissected from the whole brain. The fatty acid content was determined in the different phospholipid fractions: phosphatidylcholine (PC), phosphatidyl-serine (PS), and phosphatidylethanolamine (PE) in the rat brain regions. In the visual discrimination test, the order of the cumulative errors made in Y-water maze test were SO > MO > ME. This suggested that the balanced diet supplemented with vitamin I had the most beneficial effect on learning ability. The overall characteristics of correlation between fatty acids and behavior development were that the frequency of cumulative errors were negatively correlated significantly with monounsaturated fatty acids (MUFAs), ie., 18:1 $\omega$9 and 22:1 $\omega$9. Docosa-hexaenoic acid (22:6 $\omega$3) of PS in frontal cortex (FC) was negatively correlated with the number of errors made in the Y-water maze test.22:5 $\omega$6 PS in hippocampus (H), PC and PE in corpus striatum (CS), PC in cerebellum (CB) were positively correlated with cumulative errors. And these errors were negatively correlated with 20:4 $\omega$ 6 of PE in corpus striatum (CS) and PC in cerebellum (CB). Especially, O1eic acid (18:1 u 9) in all phospholipid fractions (PC, PS, PE) of hippocampus was negatively correlated with the number of errors. These findings demonstrate that the MUFAs were might be essential for proper brain development, especially in hippocampus which is generally thought to be the regions of memory and learning.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.291-297
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• 2001

For a stochastic regression model in which the errors are assumed to form a stationary linear process, we show that the difference between the empirical distribution functions of the errors and the estimates of those errors converges uniformly in probability to zero at the rate of $o_{p}$ ( $n^{-}$$\frac{1}{2}$) as the sample size n increases.

• Journal of the Korean Statistical Society
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• 제36권4호
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• pp.523-542
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• 2007

In this paper we consider semiparametric random effect panel models that contain AR(p) disturbances. We derive the efficient score function and the information bound for estimating the slope parameters. We make minimal assumptions on the distribution of the random errors, effects, and the regressors, and provide semiparametric efficient estimates of the slope parameters. The present paper extends the previous work of Park et al.(2003) where AR(1) errors were considered.

• 품질경영학회지
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• 제26권4호
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• pp.143-150
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• 1998

We propose an adaptive monitoring a, pp.oach for serially correlated data. This algorithm uses the adaptive linear prediction lattice filter (ALPLF) which makes it compute process parameters in real time and recursively update their estimates. It involves computation of the forward and backward prediction errors. CUSUM control charts are a, pp.ied to prediction errors simulaneously in both directions as an omnibus method for detecting changes in process parameters. Results of computer simulations demonstrate that the proposed adaptive monitoring a, pp.oach has great potentials for real-time industrial a, pp.ications, which vary frequently in their control environment.