• Title/Summary/Keyword: Parametric error

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Comprehensive studies of Grassmann manifold optimization and sequential candidate set algorithm in a principal fitted component model

  • Chaeyoung, Lee;Jae Keun, Yoo
    • Communications for Statistical Applications and Methods
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    • v.29 no.6
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    • pp.721-733
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    • 2022
  • In this paper we compare parameter estimation by Grassmann manifold optimization and sequential candidate set algorithm in a structured principal fitted component (PFC) model. The structured PFC model extends the form of the covariance matrix of a random error to relieve the limits that occur due to too simple form of the matrix. However, unlike other PFC models, structured PFC model does not have a closed form for parameter estimation in dimension reduction which signals the need of numerical computation. The numerical computation can be done through Grassmann manifold optimization and sequential candidate set algorithm. We conducted numerical studies to compare the two methods by computing the results of sequential dimension testing and trace correlation values where we can compare the performance in determining dimension and estimating the basis. We could conclude that Grassmann manifold optimization outperforms sequential candidate set algorithm in dimension determination, while sequential candidate set algorithm is better in basis estimation when conducting dimension reduction. We also applied the methods in real data which derived the same result.

The Controller Design for Lane Following with 3-Degree of Freedom Vehicle Dynamics (3자유도 차량모델을 이용한 차선추종 µ 제어기 설계)

  • Ji, Sang-Won;Lim, Tae-Woo;You, Sam-Sang;Kim, Hwan-Seong
    • Journal of Power System Engineering
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    • v.17 no.3
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    • pp.72-81
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    • 2013
  • Many articles have been published about a 2-degree of freedom model that includes the lateral and yaw motions for controller synthesis in intelligent transport system applications. In this paper, a 3-degree of freedom linear model that includes the roll motion is developed to design a robust steering controller for lane following maneuvers using ${\mu}$-synthesis. This linear perturbed system includes a set of parametric uncertainties in cornering stiffness and unmodelled dynamics in steering actuators. The state-space model with parametric uncertainties is represented in linear fractional transformation form. Design purpose can be obtained by properly choosing the frequency dependent weighting functions. The objective of this study is to keep the tracking error and steering input energy small in the presence of variations of the cornering stiffness coefficients. Furthermore, good ride quality has to be achieved against these uncertainties. Frequency-domain analyses and time-domain numerical simulations are carried out in order to evaluate these performance specifications of a given vehicle system. Finally, the simulation results indicate that the proposed robust controller achieves good performance over a wide range of uncertainty for the given maneuvers.

Parametric Analysis of the Solar Radiation Pressure Model for Precision GPS Orbit Determination

  • Bae, Tae-Suk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.1
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    • pp.55-62
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    • 2017
  • The SRP (Solar Radiation Pressure) model has always been an issue in the dynamic GPS (Global Positioning System) orbit determination. The widely used CODE (Center for Orbit Determination in Europe) model and its variants have nine parameters to estimate the solar radiation pressure from the Sun and to absorb the remaining forces. However, these parameters show a very high correlation with each other and, therefore, only several of them are estimated at most of the IGS (International GNSS Service) analysis centers. In this study, we attempted to numerically verify the correlation between the parameters. For this purpose, a bi-directional, multi-step numerical integrator was developed. The correlation between the SRP parameters was analyzed in terms of post-fit residuals of the orbit. The integrated orbit was fitted to the IGS final orbit as external observations. On top of the parametric analysis of the SRP parameters, we also verified the capabilities of orbit prediction at later time epochs. As a secondary criterion for orbit quality, the positional discontinuity of the daily arcs was also analyzed. The resulting post-fit RMSE (Root-Mean-Squared Error) shows a level of 4.8 mm on average and there is no significant difference between block types. Since the once-per-revolution parameters in the Y-axis are highly correlated with those in the B-axis, the periodic terms in the D- and Y-axis are constrained to zero in order to resolve the correlations. The 6-hr predicted orbit based on the previous day yields about 3 cm or less compared to the IGS final orbit for a week, and reaches up to 6 cm for 24 hours (except for one day). The mean positional discontinuity at the boundary of two 1-day arcs is on the level of 1.4 cm for all non-eclipsing satellites. The developed orbit integrator shows a high performance in statistics of RMSE and positional discontinuity, as well as the separations of the dynamic parameters. In further research, additional verification of the reference frame for the estimated orbit using SLR is necessary to confirm the consistency of the orbit frames.

Comparison of Single Imputation Methods in 2×2 Cross-Over Design with Missing Observations (2×2 교차계획법에서 결측치가 있을 때의 결측치 처리 방법 비교에 관한 연구)

  • Jo, Bobae;Kim, Dongjae
    • The Korean Journal of Applied Statistics
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    • v.28 no.3
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    • pp.529-540
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    • 2015
  • A cross-over design is frequently used in clinical trials (especially in bioequivalence tests with a parametric method) for the comparison of two treatments. Missing values frequently take place in cross-over designs in the second period. Usually, subjects that have missing values are removed and analyzed. However, it can be unsuitable in clinical trials with a small sample size. In this paper, we compare single imputation methods in a $2{\times}2$ cross-over design when missing values exist in the second period. Additionally, parametric and nonparametric methods are compared after applying single imputation methods. A Monte-Carlo simulation study compares type I error and the power of methods.

Development of a Storage-Reliability Estimation Method Using Quantal Response Data for One-Shot Systems with Low Reliability-Decreasing Rates (미소한 신뢰도 감소율을 가지는 원샷 시스템의 가부반응 데이터를 이용한 저장 신뢰도 추정방법 개발)

  • Jang, Hyun-Jeung;Son, Young-Kap
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.10
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    • pp.1291-1298
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    • 2011
  • This paper proposes a new reliability estimation method for one-shot systems using quantal response data, which is based on a parametric estimation method. The proposed method considers the time-variant failure ratio of the quantal response data and it can overcome the problems in parametric estimation methods. Seven reliability estimation methods in the literature were compared with the proposed method in terms of the accuracy of reliability estimation in order to verify the proposed method. To compare the accuracy of reliability estimation, the SSEs (Sum of Squared Error) of the reliability estimation results for the different estimation methods were evaluated according to the various numbers of samples tested. The proposed method provided more accurate reliability estimation results than any of the other methods from the results of the accuracy comparison.

Process for Risk Severity Estimation of Weapon System Development Project using Parametric Estimation Method/Linear Kalman Filter (모수 추정기법/선형 칼만 필터를 이용한 무기체계개발 프로젝트 위험 요소의 영향도 추정 프로세스)

  • Lee, Seung-Yup
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.6
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    • pp.567-574
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    • 2018
  • Risk management is a method to 1) identify risks that can adversely affect the cost, schedule, and target achievement performance of a system development project, and 2) manage the identified risks based on the severity and likelihood assigned to each risk item. Risk management is applicable to various fields, since it can manage the cost/schedule and effectively guides accomplishing the target performance by identifying and managing the risks in advance, which necessitates many concurrent studies. This paper proposes a procedure to estimate the severity value for a risk item using a Kalman filter. It is assumed that the severity can be expressed as an equation consisting of cost/schedule loss during the risk event. A linear Kalman filter is used to reduce the error between the true and estimated values, which can eventually save resources spent on the risk management procedure. A simulation test case was conducted to demonstrate the validity of the proposed method.

Estimation of smooth monotone frontier function under stochastic frontier model (확률프런티어 모형하에서 단조증가하는 매끄러운 프런티어 함수 추정)

  • Yoon, Danbi;Noh, Hohsuk
    • The Korean Journal of Applied Statistics
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    • v.30 no.5
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    • pp.665-679
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    • 2017
  • When measuring productive efficiency, often it is necessary to have knowledge of the production frontier function that shows the maximum possible output of production units as a function of inputs. Canonical parametric forms of the frontier function were initially considered under the framework of stochastic frontier model; however, several additional nonparametric methods have been developed over the last decade. Efforts have been recently made to impose shape constraints such as monotonicity and concavity on the non-parametric estimation of the frontier function; however, most existing methods along that direction suffer from unnecessary non-smooth points of the frontier function. In this paper, we propose methods to estimate the smooth frontier function with monotonicity for stochastic frontier models and investigate the effect of imposing a monotonicity constraint into the estimation of the frontier function and the finite dimensional parameters of the model. Simulation studies suggest that imposing the constraint provide better performance to estimate the frontier function, especially when the sample size is small or moderate. However, no apparent gain was observed concerning the estimation of the parameters of the error distribution regardless of sample size.

Evaluation on Flexural Performance of Precast Decks with Ribbed Joint by FEM (유한요소해석에 의한 요철형 이음단면을 갖는 프리캐스트 바닥판의 휨성능 평가)

  • Oh, Hyun-Chul;Chung, Chul-Hun;Kang, Myoung-Gu;Park, Se-Jin;Shin, Dong-Ho
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.20 no.1
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    • pp.85-94
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    • 2016
  • In this study, a non-linear FEM model is presented to predict the static flexural performance of precast bridge decks with ribbed joint and is verified with previous experiment results through comparison. The several theory of material properties were applied to each mechanical properties in FEM model and FEM model's input variables were determined through experiment result and parametric study. The FEM results showed good accuracy in predicting the structural performance of the specimens and FEM model's average error rate was 5%. Also, each specimen's cracking aspect and failure mode can be predicted through FEM's plastic strain distribution. Thus, this FEM model can be used effectively for predicting the ultimate behavior and parametric study to development of design formula for joint.

Power study for 2 × 2 factorial design in 4 × 4 latin square design (4 × 4 라틴방격모형 내 2 × 2 요인모형의 검정력 연구)

  • Choi, Young Hun
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.6
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    • pp.1195-1205
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    • 2014
  • Compared with single design, powers of rank transformed statistic for testing main and interaction effects for $2{\times}2$ factorial in $4{\times}4$ latin square design are rapidly increased as effect size and replication size are increased. In general powers of rank transformed statistic are superior without regard to the diversified effect composition and the type of error distributions as nontesting factors are few and effect size are small. Powers of rank transformed statistic show much higher level than those of parametric statistic in exponential and double exponential distributions. Further powers of rank transformed statistic are very similar with those of parametric statistic in normal and uniform distributions.

A Study on Accuracy of Meteorological Information for Low Altitude Aerospace around the Airport on the West Coast (서해안 인접공항의 저고도 항공기상 정확도 연구)

  • Cho, Young-Jin;Yoo, Kwang Eui
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.28 no.2
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    • pp.53-62
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    • 2020
  • This study is to evaluate the accuracy of the meteorological information provided for the aircraft operating at low altitude. At first, it is necessary to identify crucial elements of weather information closely related to flight safety during low altitude flights. The study conducted a survey of pilots of low altitude aircraft, divided into pre-flight and in-flight phases, and reached an opinion that wind direction, wind speed, cloud coverage and ceiling and visibility are important items. Related to these items, we compared and calculated the accuracy of TAFs and METARs from Taean Airfield, Seosan Airport and Gunsan Airport because of their high number of domestic low-altitude flights. Accuracy analysis evaluated the accuracy of two numerical variables, Mean Absolute Error(MAE) and Root Mean Square Error(RMSE), and the cloud coverage which is categorical variable was calculated and compared by accuracy. For numeric variables, one-way ANOVA, which is a parameter-test, was approached to identify differences between actual forecast values and observations based on absolute errors for each item derived from the results of MAE and RMSE accuracy analyses. To determine the satisfaction of both normality assumptions and equivalence variability assumptions, the Shapiro-Wilk test was performed to verify that they do not have a normality distribution for numerical variables, and for the non-parametric test, Kruscal-Wallis test was conducted to determine whether or not they are satisfied.