• Communications for Statistical Applications and Methods
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• 제29권5호
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• pp.615-627
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• 2022

Principal Fitted Component (PFC) is a semi-parametric sufficient dimension reduction (SDR) method, which is originally proposed in Cook (2007). According to Cook (2007), the PFC has a connection with other usual non-parametric SDR methods. The connection is limited to sliced inverse regression (Li, 1991) and ordinary least squares. Since there is no direct comparison between the two approaches in various forward regressions up to date, a practical guidance between the two approaches is necessary for usual statistical practitioners. To fill this practical necessity, in this paper, we newly derive a connection of the PFC to covariance methods (Yin and Cook, 2002), which is one of the most popular SDR methods. Also, intensive numerical studies have done closely to examine and compare the estimation performances of the semi- and non-parametric SDR methods for various forward regressions. The founding from the numerical studies are confirmed in a real data example.

• 대한토목학회논문집
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• 제9권1호
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• pp.97-107
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• 1989

본 연구에서는 falling weight deflectometer(FWD)시험의 표면 처짐곡선으로부터 3층 아스팔트 포장 구조체의 물성을 추정할 수 있는 역산반복기법을 개발하였다. 안정처리기층과 쇄석기층을 갖는 포장구조체에 대한 요소설계를 실시하여 일련의 해석모델을 설정하고, 다층탄성해석에 의해 이들 해석모델의 이론적 처짐곡선을 산정하여 처짐특성 분석 및 탄성계수 추정식을 구하였다. 반복역산시 추정식에 의한 각 층 탄성계수를 초기 가정치로 하고, 탄성계수 변화율과 처짐 변화율의 관계를 구하여 이들 탄성계수 보정에 사용하였다. 다층탄성해석은 전산 프로그램 SINELA를 이용하였다. 처짐특성 분석을 통한 보다 효율적인 역산반복기법을 전산화하였으며, 수치모델을 통해 그 신뢰성 및 적용성을 검증하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제17권3호
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• pp.1261-1264
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• 2016

Background: In breast cancer (BC), it has been suggested that nuclear overexpression of p53 protein might be an indicator of poor prognosis. The aim of the current study was to evaluate the expression of p53 BC in Kurdish women from the West of Iran and its correlation with other clinicopathology figures. Materials and Methods: In the present retrospective study, 231 patients were investigated for estrogen receptor (ER) and progesterone receptor (PR) positivity, defined as ${\geq}10%$ positive tumor cells with nuclear staining. A binary logistic regression model was selected using Akaike Information Criteria (AIC) in stepwise selection for determination of important factors. Results: ER, PR, the human epidermal growth factor receptor 2 (HER2) and p53 were positive in 58.4%, 55.4%, 59.7% and 45% of cases, respectively. Ki67 index was divided into two groups: 54.5% had Ki67<20% and 45.5% had Ki67 ${\geq}20%$. Of 214 patients, 137(64%) had lymph node metastasis and of 186 patients, 122(65.6%) had vascular invasion. Binary logistic regression analysis showed that there was inverse significant correlation between lymph node metastasis (P=0.008, OR 0.120 and 95%CI 0.025-0.574), ER status (P=0.006, OR 0.080, 95%CI 0.014-0.477) and a direct correlation between HER2 (P=005, OR 3.047, 95%CI 1.407-6.599) with the expression of p53. Conclusions: As in a number of studies, expression of p53 had a inverse correlation with lymph node metastasis and ER status and also a direct correlation with HER2 status. Also, p53-positivity is more likely in triple negative BC compared to other subtypes.

• 응용통계연구
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• 제29권1호
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• pp.181-192
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• 2016

옵션의 가격을 결정하는 문제에서 블랙-숄즈 모형이 가지는 단점을 보완하기 위해 블랙-숄즈 가격을 선도항으로 하여 보정항을 구하는 근사적 옵션가격의 결정방법을 고려하였다. 이러한 근사적 가격결정 방법들은 비교적 적은 자료를 가지고 간단한 계산으로 다양한 형태의 위험중립 확률분포에 의한 옵션가격을 계산할 수 있다. 이 논문에서는 일반적으로 관찰되는 시장상황을 모사한 모의실험과 실제 시장에서 관측되는 KOSPI200 옵션가격 자료를 통해 몇 가지 근사방법들의 적합성과를 비교, 평가하였다. 헤르미트 다항식 계열의 Edgeworth 확장과 A-type Gram-Charlier, C-type Gram-Charlier 방법, NIG 분포를 이용하는 방법, 비선형 회귀를 이용한 점근적 근사방법이 고려되었다. 모의실험에서는 순수 점프 레비 확률과정 가운데 옵션가격이 닫힌 해의 형태로 존재하는 Variance gamma 과정을 가정하여 자료를 생성하였다. 모의실험과 실제 자료분석의 결과, 분포함수를 먼저 근사하여 가격을 계산하는 것보다 근사적 가격식을 유도하여 직접 가격을 근사하는 방법들의 성능이 좀 더 좋았으며, 그 가운데 비선형 회귀를 이용한 점근적 근사방법이 상대적으로 좋은 성능을 보였다.

• 한국기후변화학회지
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• 제6권4호
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• pp.331-344
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• 2015

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.

• Communications for Statistical Applications and Methods
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• 제29권2호
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• pp.177-191
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• 2022

This paper addresses the use of machine learning methods for causal estimation of treatment effects from observational data. Even though conducting randomized experimental trials is a gold standard to reveal potential causal relationships, observational study is another rich source for investigation of exposure effects, for example, in the research of comparative effectiveness and safety of treatments, where the causal effect can be identified if covariates contain all confounding variables. In this context, statistical regression models for the expected outcome and the probability of treatment are often imposed, which can be combined in a clever way to yield more efficient and robust causal estimators. Recently, targeted maximum likelihood estimation and causal random forest is proposed and extensively studied for the use of data-adaptive regression in estimation of causal inference parameters. Machine learning methods are a natural choice in these settings to improve the quality of the final estimate of the treatment effect. We explore how we can adapt the design and training of several machine learning algorithms for causal inference and study their finite-sample performance through simulation experiments under various scenarios. Application to the percutaneous coronary intervention (PCI) data shows that these adaptations can improve simple linear regression-based methods.

• 한국전문물리치료학회지
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• 제8권3호
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• pp.63-76
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• 2001

Many studies have shown that the initial median frequency (MDF) and slope correlate with the muscle fiber composition. This study tested the hypothesis that the initial MDF and slope are fixed, regardless of the interval at which data are collected. MDF data using moving fast Fourier transformation of EMG signals, following local fatigue induced by isotonic exercise, were obtained. An inverse FFT was used to eliminate noise, and characteristic decreasing regression lines were obtained. The regression analysis was done in three different periods, the first one third, first half, and full period, looking at variance in the initial MDF, slope, and fatigue index. Data from surface EMG signals during fatiguing isotonic exercise of the biceps brachii and vastus lateralis in 20 normal subjects were collected. The loads tested were 30% and 60% maximum voluntary contraction (MVC) in the biceps brachii and 40% and 80% MVC in the vastus lateralis. The rate was 25 flexions per minute. There were no significant differences in the initial MDF or slope during the early or full periods of the regression, but there was a significant difference in the fatigue index. Therefore, to observe the change in the initial MDF and slope of the MDF regression line during isotonic exercise, this study suggest that only the early interval need to be observed.

• 대한전기학회논문지:전력기술부문A
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• 제54권2호
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• pp.79-87
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• 2005

At present Cournot model is one of the most commonly used theories to analyze the gaming situation in oligopoly market. But there exist several problems to apply this model to electricity market. The representative one is to obtain the inverse demand curve able to be induced from the relationship between market price and demand response. In Cournot model, each player offers their generation quantity to accomplish maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears on the long-term basis through the statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium.

• Asian Pacific Journal of Cancer Prevention
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• 제15권13호
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• pp.5161-5166
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• 2014

Our aim was to access the association between recreational physical activity (RPA) and risk of ovarian cancer (OC). The studies were retrieved from the PubMed and Embase databases up to February 20th, 2014. Risk ratios (OR) and 95% confidence intervals (CI) were used to estimate effect sizes. Random-effects or fixed-effects models were used to pool the data. The trim and fill method was applied for sensitivity analysis. Begg's rank correlation test and Egger's regression asymmetry test were employed to assess the publication bias. A total of 6 studies (435398 participants including 2983 OC patients) were included in this meta-analysis. The overall estimate indicated that there was weakly inverse association between RPA and OC risk (RR=0.90, 95%CI: 0.72-1.12, p=0.335). Meanwhile, for prospective cohort studies, a result consistent with the overall estimate was obtained (RR=1.12, 95% CI: 0.88-1.42, p=0.356). However, for case control studies, the pooled estimate of RR was 0.76 (95%CI: 0.64-0.90, p=0.002), indicating a clear significant association between RPA and OC risk. In addition, the sensitivity analysis indicated a significant link between RPA and risk of OC after removing Lahmann's study (RR=0.80, 95% CI: 0.68-0.93, p=0.004). No significant publication bias was found (Begg's test: p=1.00; Egger's test: p=0.817). In conclusion, our meta-analysis indicated a weakly inverse relationship between RPA and the occurrence of OC.

• Asian Pacific Journal of Cancer Prevention
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• 제17권sup3호
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• pp.305-309
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• 2016

PTEN protein is an important tumour suppressor factor detectable by immunohistochemistry. The goal of the present study was to investigate the prognostic role of PTEN gene expression focusing on length of survival in breast cancer patients. This descriptive-analytical study was conducted on 100 breast cancer cases referred to Sabzevar hospitals in the north east of Iran between 2010 and 2011, followed up to 2015. The PTEN gene expression of tumour tissue samples was determined using specific monoclonal antibodies. The data were analyzed using Chi-square test and Fisher's exact test. Patient length of survival was analyzed after 4 years of follow-up using the Cox regression model. The PTEN gene was expressed in 70 of 100 samples, while being found at a high level in all noncancerous samples. There was an inverse significant relationship between expression of PTEN and tumour stage and grade (p<0.001). In addition, expression of PTEN in invasive ductal tumours was less than in non-invasive tumours. There was also an inverse significant relationship between the likelihood of death and PTEN gene expression (p<0.01). These findings indicate that lack of PTEN gene expression can be sign for a worse prognosis and poor survival in breast cancer.