• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.559-564
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• 2016

The Durbin-Watson (DW) test in regression model and the Ljung-Box (LB) test in ARMA (autoregressive moving average) model are typical examples of correlated error tests. The DW test is used for detecting autocorrelation of errors using the residuals from a regression analysis. The LB test is used for specifying the correct ARMA model using the first some sample autocorrelations based on the residuals of a tted ARMA model. In this article, simulations with four data generating processes have been carried out to evaluate their performances as correlated error tests. Our simulations show that the DW test is severely dependent on the assumed AR(1) model but isn't sensitive enough to reject the misspecified model and that the LB test reports lackluster performance in general.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.3
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• pp.291-295
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• 2008

We have developed an evaluation technique for ratio errors of current transformer (CT) comparator by using the precise standard capacitors. By applying this technique for equivalent circuit of CT comparator evaluation system, we can obtain the calculated and measured ratio errors in the CT comparator. Thus we can evaluate ratio errors of CT comparator by comparing the calculated and measured ratio errors. Because this method requires only the standard capacitors, it is simple and easy method to reliability and accuracy maintenance of CT comparator. The method was applied to CT comparator under test with the ratio error ranges of $0{\sim}{\pm}10%$. The ratio error of the CT comparator under test theoretically obtained in this method are consistent with that measured for same CT comparator under test by using wide ratio error CT within an estimated expanded uncertainty (k = 2) in the overall ratio error ranges.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.3
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• pp.143-151
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• 2001

Machine tool errors have to be characterized and predicted to improve machine tool accuracy. A real-time error compensation system has been developed based on volumetric error synthesis model which is composed of machine tool errors. This paper deals with new algorithm about verification of machine tool errors. This new algorithm uses a simplified volumetric error synthesis model. This simplified model is constructed with only main components among the error components of the machine. The main error components are analyzed by ball bar test of hemispherical helix. The novel measurement method using ball bar system has many advantages which are more efficient, easier to use than conventional measurement system.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.4 no.3
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• pp.58-66
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• 1995

It is very important to test motion accuracy and performance of NC machine tools as they affect that of all other machines machined by them in industry. In this paper, in has become possible to detect errors of linear displacement of radial direction for circular motion test using newly assembled magnetic type of linear scales so called Magnescale ball bar system, and to calculate time interval getting error motion data and revolution angle of circular motion in machining center using tick pulses come out from computer. And a set of error data gotten from test is expressed to a plot by computer treatment and to numerics of error motion by statistical treatment and results of test are compared with those of Renishaw ball bar system.

• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.1878-1886
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• 2021

For industrial package (IP)-type transport containers for radioactive materials, a free drop test should be conducted under regulatory conditions. Owing to various uncertainties observed during the drop test, errors in drop angles inevitably occur. In IP-type metal transport containers in which the container directly impacts onto a rigid target without any shock absorbing materials, the error in the drop angle due to a slight misalignment makes a significant difference from the ideal drop. In particular, in a vertical drop, the error in the drop angle causes a strong secondary impact. In this paper, a numerical method is proposed to estimate the error in the drop angle occurring during the test. To determine this error, an optimization method accompanying a computational drop analysis is proposed, and a surrogate model is introduced to ensure calculation efficiency. Effectiveness of the proposed method is validated by performing the verification and comparison between the test and the analysis applied with the drop angle error.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.57-69
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• 2022

Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among them, the purpose of Adaptive Cruise Control (ACC) is to minimize the driver's driving fatigue through the control of the vehicle's longitudinal speed and relative distance. In this study, for the research of the ACC test in the real environment, the real-road test was conducted based on domestic-road test scenario proposed in preceding study, considering ISO 15622 test method. In this case, the distance measurement method using the dual camera was verified by comparing and analyzing the result of using the dual camera and the result of using the measurement equipment. As a result of the comparison, two results could be derived. First, the relative distance after stabilizing the ACC was compared. As a result of the comparison, it was found that the minimum error rate was 0.251% in the first test of scenario 8 and the maximum error rate was 4.202% in the third test of scenario 9. Second, the result of the same time was compared. As a result of the comparison, it was found that the minimum error rate was 0.000% in the second test of scenario 10 and the maximum error rate was 9.945% in the second test of scenario 1. However, the average error rate for all scenarios was within 3%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. There were problems such as shaking caused by road surface vibration and air resistance during driving, changes in ambient brightness, and the process of focusing the video. Accordingly, it was determined that the result of calculating the distance to the preceding vehicle in the image where the problem occurred was incorrect. In the development stage of ADAS such as ACC, it is judged that only dual cameras can reduce the cost burden according to the above derivation of test results.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.489-501
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• 1999

In this paper, we consider the panel data regression model in which the disturbances have nested error component. We derive a Lagrange Multiplier(LM) test which is jointly testing for the presence of random individual effects and nested effects under the normality assumption of the disturbances. This test extends the earlier work of Breusch and Pagan(1980) and Baltagi and Li(1991). Further, it is shown that this LM test has the same asymptotic distribution without normality assumption of the disturbances.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.183-186
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• 2007

We introduction some properties for fuzzy power function of performance of a test. First we define fuzzy type I error and type II error for the probability of the two types of error. And we show that an fuzzy error probability of one kind can only be reduced at cost of increasing the other fuzzy error probability.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.69.2-69
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• 2002

Process measurements contain random and gross errors and the size estimation of gross errors is required for production accounting. Mixed integer programming technique had been applied to identify and estimate the gross errors simultaneously. However, the compensate model based on mixed integer programming used all measured variables or spanning tree as gross error candidates. This makes gross error estimation problem combinatorial or computationally expensive. Mixed integer programming with test statistics is proposed for computationally inexpensive gross error identification /estimation. The gross error candidates are identified by measurement test and the set of gross error candidates are...

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.296-302
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• 1995

When heteroscedasticity occurs in random effects linear model, the error variance may depend on the values of one or more of the explanatory variables or on other relevant quantities such as time or spatial ordering. In this paper we derive a score test as a diagnostic tool for detecting non-constant error variance in random effefts linear model based on the model expansion on error variance. This score test is compared to loglikelihood ratio test.