• Title/Summary/Keyword: Linear spline

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A Second Order Smoother (이차 평활스플라인)

  • 김종태
    • The Korean Journal of Applied Statistics
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    • v.11 no.2
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    • pp.363-376
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    • 1998
  • The linear smoothing spline estimator is modified to remove boundary bias effects. The resulting estimator can be calculated efficiently using an O(n) algorithm that is developed for the computation of fitted values and associated smoothing parameter selection criteria. The asymptotic properties of the estimator are studied for the case of a uniform design. In this case the mean squared error properties of boundary corrected linear smoothing splines are seen to be asymptotically competitive with those for standard second order kernel smoothers.

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Derivation of a benchmark dose lower bound of lead for attention deficit hyperactivity disorder using a longitudinal data set (경시적 자료의 주의력 결핍 과잉행동 장애를 종점으로 한 납의 벤치마크 용량 하한 도출)

  • Lee, Juhyung;Kim, Si Yeon;Ha, Mina;Kwon, Hojang;Kim, Byung Soo
    • The Korean Journal of Applied Statistics
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    • v.29 no.7
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    • pp.1295-1309
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    • 2016
  • This paper is to reproduce the result of Kim et al. (2014) by deriving a benchmark dose lower bound (BMDL) of lead based on the 2005 cohort data set of Children's Health and Environmental Research (CHEER) data set. The ADHD rating scales in the 2005 cohort were not consistent along the three follow-ups since two different ADHD rating scales were used in the cohort. We first unified the ADHD rating scales in the 2005 cohort by deriving a conversion formula using a penalized linear spline. We then constructed two linear mixed models for the 2005 cohort which reflected the longitudinal characteristics of the data set. The first model introduced the random intercept and the random slope terms and the second model assumed the first order autoregressive structure of the error term. Using these two models, we derived the BMDLs of lead and reconfirmed the "regression to the mean" nature of the ADHD score discovered by Kim et al. (2014). We also noticed that there was a definite difference between the sampling distributions of the two cohorts. As a result, taking this difference into account, we were able to obtain the consistent result with Kim et al. (2014).

A Baseline Correction for Effective Analysis of Alzheimer’s Disease based on Raman Spectra from Platelet (혈소판 라만 스펙트럼의 효율적인 분석을 위한 기준선 보정 방법)

  • Park, Aa-Ron;Baek, Sung-June
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.49 no.1
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    • pp.16-22
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    • 2012
  • In this paper, we proposed a method of baseline correction for analysis of Raman spectra of platelets from Alzheimer's disease (AD) transgenic mice. Measured Raman spectra include the meaningful information and unnecessary noise which is composed of baseline and additive noise. The Raman spectrum is divided into the local region including several peaks and the spectrum of the region is modeled by curve fitting using Gaussian model. The additive noise is clearly removed from the process of replacing the original spectrum with the fitted model. The baseline correction after interpolating the local minima of the fitted model with linear, piecewise cubic Hermite and cubic spline algorithm. The baseline corrected models extract the feature with principal component analysis (PCA). The classification result of support vector machine (SVM) and maximum $a$ posteriori probability (MAP) using linear interpolation method showed the good performance about overall number of principal components, especially SVM gave the best performance which is about 97.3% true classification average rate in case of piecewise cubic Hermite algorithm and 5 principal components. In addition, it confirmed that the proposed baseline correction method compared with the previous research result could be effectively applied in the analysis of the Raman spectra of platelet.

A Study on the Improvement of Digital Periapical Images using Image Interpolation Methods (영상보간법을 이용한 디지털 치근단 방사선영상의 개선에 관한 연구)

  • Song Nam-Kyu;Koh Kawng-Joon
    • Journal of Korean Academy of Oral and Maxillofacial Radiology
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    • v.28 no.2
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    • pp.387-413
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    • 1998
  • Image resampling is of particular interest in digital radiology. When resampling an image to a new set of coordinate, there appears blocking artifacts and image changes. To enhance image quality, interpolation algorithms have been used. Resampling is used to increase the number of points in an image to improve its appearance for display. The process of interpolation is fitting a continuous function to the discrete points in the digital image. The purpose of this study was to determine the effects of the seven interpolation functions when image resampling in digital periapical images. The images were obtained by Digora, CDR and scanning of Ektaspeed plus periapical radiograms on the dry skull and human subject. The subjects were exposed to intraoral X-ray machine at 60kVp and 70 kVp with exposure time varying between 0.01 and 0.50 second. To determine which interpolation method would provide the better image, seven functions were compared; (1) nearest neighbor (2) linear (3) non-linear (4) facet model (5) cubic convolution (6) cubic spline (7) gray segment expansion. And resampled images were compared in terms of SNR(Signal to Noise Ratio) and MTF(Modulation Transfer Function) coefficient value. The obtained results were as follows ; 1. The highest SNR value(75.96dB) was obtained with cubic convolution method and the lowest SNR value(72.44dB) was obtained with facet model method among seven interpolation methods. 2. There were significant differences of SNR values among CDR, Digora and film scan(P<0.05). 3. There were significant differences of SNR values between 60kVp and 70kVp in seven interpolation methods. There were significant differences of SNR values between facet model method and those of the other methods at 60kVp(P<0.05), but there were not significant differences of SNR values among seven interpolation methods at 70kVp(P>0.05). 4. There were significant differences of MTF coefficient values between linear interpolation method and the other six interpolation methods (P< 0.05). 5. The speed of computation time was the fastest with nearest -neighbor method and the slowest with non-linear method. 6. The better image was obtained with cubic convolution, cubic spline and gray segment method in ROC analysis. 7. The better sharpness of edge was obtained with gray segment expansion method among seven interpolation methods.

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Estimating dose-response curves using splines: a nonparametric Bayesian knot selection method

  • Lee, Jiwon;Kim, Yongku;Kim, Young Min
    • Communications for Statistical Applications and Methods
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    • v.29 no.3
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    • pp.287-299
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    • 2022
  • In radiation epidemiology, the excess relative risk (ERR) model is used to determine the dose-response relationship. In general, the dose-response relationship for the ERR model is assumed to be linear, linear-quadratic, linear-threshold, quadratic, and so on. However, since none of these functions dominate other functions for expressing the dose-response relationship, a Bayesian semiparametric method using splines has recently been proposed. Thus, we improve the Bayesian semiparametric method for the selection of the tuning parameters for splines as the number and location of knots using a Bayesian knot selection method. Equally spaced knots cannot capture the characteristic of radiation exposed dose distribution which is highly skewed in general. Therefore, we propose a nonparametric Bayesian knot selection method based on a Dirichlet process mixture model. Inference of the spline coefficients after obtaining the number and location of knots is performed in the Bayesian framework. We apply this approach to the life span study cohort data from the radiation effects research foundation in Japan, and the results illustrate that the proposed method provides competitive curve estimates for the dose-response curve and relatively stable credible intervals for the curve.

Analysis of Linear Springing Responses of a Container Carrier by using Vlasov Beam Model (Vlasov 보 모델을 이용한 컨테이너 선박의 스프링잉 응답해석)

  • Kim, Yoo-Il;Kim, Yong-Hwan
    • Journal of the Society of Naval Architects of Korea
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    • v.47 no.3
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    • pp.306-320
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    • 2010
  • Modern ultra-large container carriers can be exposed to the unprecedented springing excitation from ocean waves due to their relatively low torsional rigidity. Large deck opening on the deck of container carriers tends to cause warping distortion of hull structure under wave-induced excitation, eventually leading to the higher chance of resonance vibration between its torsional response and incoming waves. To handle this problem, a higher-order B-spline Rankine panel method and Vlasov-beam FE model was directly coupled in the time domain, and the coupled equation was solved by using an implicit iterative method. In order to capture the complicated behavior of thin-walled open section girder, a sophisticated beam-based finite element model was developed, which takes into account warping distortion and shear-on-wall effect. Then, the developed beam model was directly coupled with the time-domain Rankine panel method for hydrodynamic problem by using the fixed-point iteration method. The developed computational scheme was validated through the comparison with the frequency-domain solution on the container carrier model in linear springing regime.

Shrinkage Small Area Estimation Using a Semiparametric Mixed Model (준모수혼합모형을 이용한 축소소지역추정)

  • Jeong, Seok-Oh;Choo, Manho;Shin, Key-Il
    • The Korean Journal of Applied Statistics
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    • v.27 no.4
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    • pp.605-617
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    • 2014
  • Small area estimation is a statistical inference method to overcome large variance due to a small sample size allocated in a small area. A shrinkage estimator obtained by minimizing relative error(RE) instead of MSE has been suggested. The estimator takes advantage of good interpretation when the data range is large. A semiparametric estimator is also studied for small area estimation. In this study, we suggest a semiparametric shrinkage small area estimator and compare small area estimators using labor statistics.

Comparison of Regression Models for Estimating Ventilation Rate of Mechanically Ventilated Swine Farm (강제환기식 돈사의 환기량 추정을 위한 회귀모델의 비교)

  • Jo, Gwanggon;Ha, Taehwan;Yoon, Sanghoo;Jang, Yuna;Jung, Minwoong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.62 no.1
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    • pp.61-70
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    • 2020
  • To estimate the ventilation volume of mechanically ventilated swine farms, various regression models were applied, and errors were compared to select the regression model that can best simulate actual data. Linear regression, linear spline, polynomial regression (degrees 2 and 3), logistic curve, generalized additive model (GAM), and gompertz curve were compared. Overfitting models were excluded even when the error rate was small. The evaluation criteria were root mean square error (RMSE) and mean absolute percentage error (MAPE). The evaluation results indicated that degree 3 exhibited the lowest error rate; however, an overestimation contradiction was observed in a certain section. The logistic curve was the most stable and superior to all the models. In the estimation of ventilation volume by all of the models, the estimated ventilation volume of the logistic curve was the smallest except for the model with a large error rate and the overestimated model.

Association between dietary omega-3 fatty acid intake and depression in postmenopausal women

  • Chae, Minjeong;Park, Kyong
    • Nutrition Research and Practice
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    • v.15 no.4
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    • pp.468-478
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    • 2021
  • BACKGROUND/OBJECTIVES: This study aimed to analyze the association between dietary omega-3 fatty acid intake and depression in postmenopausal women using data from the Korea National Health and Nutrition Examination Survey (KNHANES) VI. SUBJECTS/METHODS: The KNHANES is a cross-sectional nationwide health and nutrition survey. Dietary data, including omega-3 fatty acids, were assessed using the 24-h recall method. Depression was evaluated using a survey questionnaire. The association between dietary omega-3 fatty acids and depression was evaluated using multivariate logistic regression analysis. Depression, according to the dietary omega-3 fatty acid intake, was expressed as the odds ratio (OR) with a 95% confidence interval (CI). A total of 4,150 postmenopausal women were included in the analysis. RESULTS: In the fully-adjusted model, the group with the highest dietary omega-3 fatty acid intake significantly showed lower prevalence of depression than the group with the lowest intake (OR, 0.52; 95% CI, 0.33-0.83); a significant linear trend was detected (P for trend = 0.04). According to the dose-response analysis using cubic restricted spline regression, this association was linear and monotonic (P for non-linearity = 0.32). CONCLUSIONS: In this study, the dietary omega-3 fatty acid intake in postmenopausal women was inversely proportional to depression in a dose-response manner. Large cohort studies are needed to verify the causality between omega-3 fatty acids and depression in Korean postmenopausal women.

Study for the Development of an Optimum Hull Form using SQP (SQP법을 이용한 최적선형개발에 대한 연구)

  • Choi, Hee-Jong;Lee, Gyoung-Woo;Yun, Soon-Dong
    • Journal of Navigation and Port Research
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    • v.30 no.10 s.116
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    • pp.869-875
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    • 2006
  • This paper presents the method for developing an optimum hull form with minimum wave resistance using SQP(sequential quadratic programming) as an optimization technique. The wave resistance is evaluated by a Rankine source panel method with non-linear free surface conditions and the ITTC 1957 friction line is used to predict the frictional resistance coefficient. The geometry of the hull surface is represented and modified using NURBS(Non-Uniform Rational B-Spline) surface patches. To verity the validity of the developed program the numerical calculations for Wigley hull and Series 60( $C_B=0.6$) hull have been performed and the results obtained by the numerical calculations have been compared with the original hulls.