• Journal of the Korean Statistical Society
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• 제19권1호
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• pp.71-79
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• 1990

In the linear model which consider both the multivariate parallel-line bioassay and the multivariate linear calibration, this paper presents a Bayesian procedure which is an extension of Hunter and Lamboy (1981) and has several advantages compared with the non Bayesian techniques. Based on the methods of this article we discuss the effect of multivariate calibration and give a numerical example.

• Journal of the Korean Statistical Society
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• 제15권2호
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• pp.107-117
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• 1986

This paper gives some new results on the multivariate linear calibration problem in the case when the controlled variable is univariate. Firstly, a condition under which one can obtain a finite closed confidence interval of $x_0$(unknown controlled variable) is suggested. Secondly, this article considers a criterion to find out whether the multivariate calibration significantly shortens the confidence interval of $x_0$ and supports this criterion by examples. Finally, a multivariate extension of the results in Lwin Maritz (1982) is given.

• 대한산업공학회지
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• 제19권2호
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• pp.35-41
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• 1993

Statistical calibration is a useful technique for achieving compatibility between two different measurement methods, and it usually consists of two steps : (1) estimation of the relationship between the standard and nonstandard measurements, and (2) prediction of future standard measurements using the estimated relationship and observed nonstandard measurements. A predictive multivariate errors-in-variables model is presented for the multivariate calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the maximum likelihood (ML) estimation method is considered. It is shown that the direct and the inverse predictors for the future unknown standard measurement are the same under ML estimation. Based upon large-sample approximations, the mean square error of the predictor is derived.

• 대한화학회지
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• 제46권4호
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• pp.309-317
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• 2002

형광분광법에 의하여 주성분 회귀분석(principal component regression, PCR)과 부분 최소자승법(Partial least squares, PLS)을 이용하여 아미노산(Tryptophan and Tyrosine)을 동시에 정량하는 방법에 대하여 연구하였다. 아미노산 혼합물의 형광 스펙트럼은 들뜸파장을257nm로 고정하여 측정하였다. 두 가지 아미노산이 서로 다른 농도로 혼합되어 있는 32개의 시료용액을 280nm∼500nm 범위에서 스펙트럼들을 얻었고 이를 이용하여 PCR과 PLS회귀모델을 얻었다. 두 가지 아미노산이 서로 다른 농도로 포함된 6개의 외부검정용 시료들의 스펙트럼들을 이용해서 회귀모델의 적합성을 검정하기 위하여 외부검정용 시료의 농도를 계산하였다. 계산된 농도를 이용하여 relative standard error of prediction($RSEP_a$)를 얻었고 같은 방법으로 overall relative standard error of prediction($RSEP_m$) 도 구하였다

• 대한화학회지
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• 제47권1호
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• pp.19-25
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• 2003

흡수 분광법에 의해 얻은 스펙트럼을 주성분분석(principal analysis, PCA) 으로 자료를 요약하여 주성분 회귀분서(principal component regression, PCR)과 부분 최소자승법(partial least squares, PLS)으로 음이온과 비이온 계면활성제(anionic and nonionic surfactant)를 동시에 정량하는 방법에 대하여 연구하였다. 두 가지 계면활성제가 서로 다른 농도로 혼합되어 있는 26개의 시료용액을 400~700 nm 범위에서 스펙트럼을 얻었고, 이를 이용하여 PCR과 PLS회귀모델을 얻었다. 두 가지 계면활성제가 서로 다른 농도로 포함된 5개의 외부검정용 시료들의 스펙트럼들을 이용해서 회귀모델의 적합성을 검정하기 위하여 외부검정용 시료의 농도를 계산하였다. 계산된 농도를 이용하여 relative standard error of prediction(RSEP$_{\alpha}$)를 구하여 회귀모델의 적합성을 검정하였다.

• 품질경영학회지
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• 제43권4호
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• pp.521-532
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• 2015

Purpose: The purpose of this study is to compare two multivariate cumulative sum (MCUSUM) charts designed for spatio-temporal surveillance in terms of not only temporal detection performance but also spatial detection performance. Method: Experiments under various configurations are designed and performed to test two CUSUM charts, namely SMCUSUM and RMCUSUM. In addition to average run length(ARL), two measures of spatial identification accuracy are reported and compared. Results: The RMCUSUM chart provides higher level of spatial identification accuracy while two charts show comparable performance in terms of ARL. Conclusion: The RMCUSUM chart has more flexibility, robustness, and spatial identification accuracy when compared to those of the SMCUSUM chart. We recommend to use the RMCUSUM chart if control limit calibration is not an urgent task.

• Communications for Statistical Applications and Methods
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• 제22권2호
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• pp.137-146
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• 2015

Singh (2013) considered the dual problem to the calibration of design weights to obtain a new generalized linear regression estimator (GREG) for the finite population total. In this work, we have made an attempt to suggest a way to use the dual calibration of the design weights in case of multi-auxiliary variables; in other words, we have made an attempt to give an answer to the concern in Remark 2 of Singh (2013) work. The same idea is also used to generalize the GREG estimator proposed by Deville and S$\ddot{a}$rndal (1992). It is not an easy task to find the optimum values of the parameters appear in our approach; therefore, few suggestions are mentioned to select values for such parameters based on a random sample. Based on real data set and under simple random sampling without replacement design, our approach is compared with other approaches mentioned in this paper and for different sample sizes. Simulation results show that all estimators have negligible relative bias, and the multivariate case of Singh (2013) estimator is more efficient than other estimators.

• Journal of Biosystems Engineering
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• 제41권1호
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• pp.51-59
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• 2016

Purpose: This study examined the performance of two spectroscopy methods and multivariate classification methods to discriminate viable pepper seeds from their non-viable counterparts. Methods: A classification model for viable seeds was developed using partial least square discrimination analysis (PLS-DA) with Fourier transform near-infrared (FT-NIR) and Raman spectroscopic data in the range of $9080-4150cm^{-1}$ (1400-2400 nm) and $1800-970cm^{-1}$, respectively. The datasets were divided into 70% to calibration and 30% to validation. To reduce noise from the spectra and compare the classification results, preprocessing methods, such as mean, maximum, and range normalization, multivariate scattering correction, standard normal variate, and $1^{st}$ and $2^{nd}$ derivatives with the Savitzky-Golay algorithm were used. Results: The classification accuracies for calibration using FT-NIR and Raman spectroscopy were both 99% with first derivative, whereas the validation accuracies were 90.5% with both multivariate scattering correction and standard normal variate, and 96.4% with the raw data (non-preprocessed data). Conclusions: These results indicate that FT-NIR and Raman spectroscopy are valuable tools for a feasible classification and evaluation of viable pepper seeds by providing useful information based on PLS-DA and the threshold value.

• 분석과학
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• 제25권4호
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• pp.214-222
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• 2012

ASTM (American Society for Testing and Materials) D6751-10은 바이오디젤의 품질 규격 뿐 아니라 분석방법 또한 제시하고 있다. 하지만 ASTM 표준에 따른 바이오디젤 및 포함된 여러 불순물의 품질 분석은 경제적, 시간적으로 부담이 크다. 본 연구는 적외선 분광분석법(infrared spectroscopy)과 다변량 통계분석법 중 하나인 PLS (partial least square method)를 이용하여 1회 측정만으로 바이오 디젤 및 불순물들의 농도를 분석하는 시스템을 개발하고자 하였다. 특히, 적외선을 이용한 분석에서 생기는 각 물질의 스펙트럼에 대한 산란 보정, 노이즈 감소 등을 위해 SNV, MSC, OSC, Savitzky-Golay 등의 4가지 전처리 방법의 성능을 비교하였다. 품질 분석에 필요한 바이오 디젤 검량 모델을 PLS로 모델링 결과, Savitzky-Golay 전처리를 하였을 때 정확도가 가장 우수함을 알았다.

• Journal of Gastric Cancer
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• 제15권4호
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• pp.262-269
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• 2015

Purpose: Intraabdominal abscess is one of the most common reasons for re-hospitalization after gastrectomy. This study aimed to develop a model for estimating the probability of intraabdominal abscesses that can be used during the postoperative period. Materials and Methods: We retrospectively reviewed the clinicopathological data of 1,564 patients who underwent gastrectomy for gastric cancer between 2010 and 2012. Twenty-six related markers were analyzed, and multivariate logistic regression analysis was used to develop the probability estimation model for intraabdominal abscess. Internal validation using a bootstrap approach was employed to correct for bias, and the model was then validated using an independent dataset comprising of patients who underwent gastrectomy between January 2008 and March 2010. Discrimination and calibration abilities were checked in both datasets. Results: The incidence of intraabdominal abscess in the development set was 7.80% (122/1,564). The surgical approach, operating time, pathologic N classification, body temperature, white blood cell count, C-reactive protein level, glucose level, and change in the hemoglobin level were significant predictors of intraabdominal abscess in the multivariate analysis. The probability estimation model that was developed on the basis of these results showed good discrimination and calibration abilities (concordance index=0.828, Hosmer-Lemeshow chi-statistic P=0.274). Finally, we combined both datasets to produce a nomogram that estimates the probability of intraabdominal abscess. Conclusions: This nomogram can be useful for identifying patients at a high risk of intraabdominal abscess. Patients at a high risk may benefit from further evaluation or treatment before discharge.