• 제목/요약/키워드: Spline regression

검색결과 67건 처리시간 0.019초

평률 회귀분석을 위한 추정 방법의 비교 (Comparison of estimation methods for expectile regression)

  • 김종민;강기훈
    • 응용통계연구
    • /
    • 제31권3호
    • /
    • pp.343-352
    • /
    • 2018
  • 설명변수가 주어졌을 때 반응변수의 평균적인 추세뿐만 아니라 극단적인 지역에서의 추세에 대해서 추정하고 싶거나 반응변수 분포의 일반적인 탐색을 위해서는 분위수 회귀분석과 평률 회귀분석을 사용할 수 있다. 본 논문에서는 평률 회귀모형의 추정을 위한 모수적 방법과 비모수적 방법의 성능을 비교하고자 한다. 이를 위해 각 추정 방법을 소개하고 여러 상황의 모의실험 및 실제자료에의 적용을 통해 비교 분석을 실시하였다. 모형에 따라 성능 차이가 있는데 자료의 형태가 복잡하여 변수 간의 관계를 유추하기 힘들 경우 비모수적으로 추정한 평률 회귀분석모형이 더욱 좋은 결과를 보였다. 일반적인 회귀분석의 경우와 달리 평률의 경우 후보가 되는 모수 모형을 상정하기 어렵다는 측면에서 볼 때, 비모수적 방법의 사용이 추천될 수 있다.

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

  • 조광곤;하태환;윤상후;장유나;정민웅
    • 한국농공학회논문집
    • /
    • 제62권1호
    • /
    • pp.61-70
    • /
    • 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.

Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression

  • Zhang, Wengang;Goh, Anthony T.C.
    • Geomechanics and Engineering
    • /
    • 제10권3호
    • /
    • pp.269-284
    • /
    • 2016
  • Simplified techniques based on in situ testing methods are commonly used to assess seismic liquefaction potential. Many of these simplified methods were developed by analyzing liquefaction case histories from which the liquefaction boundary (limit state) separating two categories (the occurrence or non-occurrence of liquefaction) is determined. As the liquefaction classification problem is highly nonlinear in nature, it is difficult to develop a comprehensive model using conventional modeling techniques that take into consideration all the independent variables, such as the seismic and soil properties. In this study, a modification of the Multivariate Adaptive Regression Splines (MARS) approach based on Logistic Regression (LR) LR_MARS is used to evaluate seismic liquefaction potential based on actual field records. Three different LR_MARS models were used to analyze three different field liquefaction databases and the results are compared with the neural network approaches. The developed spline functions and the limit state functions obtained reveal that the LR_MARS models can capture and describe the intrinsic, complex relationship between seismic parameters, soil parameters, and the liquefaction potential without having to make any assumptions about the underlying relationship between the various variables. Considering its computational efficiency, simplicity of interpretation, predictive accuracy, its data-driven and adaptive nature and its ability to map the interaction between variables, the use of LR_MARS model in assessing seismic liquefaction potential is promising.

Detecting Influential Observations on the Smoothing Parameter in Nonparametric Regression

  • Kim, Choong-Rak;Jeon, Jong-Woo
    • Journal of the Korean Statistical Society
    • /
    • 제24권2호
    • /
    • pp.495-506
    • /
    • 1995
  • We present formula for detecting influential observations on the smoothing parameter in smoothing spline. Further, we express them as functions of basic building blocks such as residuals and leverage, and compare it with the local influence approach by Thomas (1991). An example based on a real data set is given.

  • PDF

유전자 알고리즘을 이용한 비모수 회귀분석

  • 김병도;노상규
    • 한국데이타베이스학회:학술대회논문집
    • /
    • 한국데이타베이스학회 1998년도 국제 컨퍼런스: 국가경쟁력 향상을 위한 디지틀도서관 구축방안
    • /
    • pp.584-594
    • /
    • 1998
  • 선형회귀분석은 가장 널리 사용되는 데이터 분석기법이지만 독립변수와 종속변수간의 관계가 선형이라고 가정하기 때문에 문제점을 가지고 있다. 비모수 회귀분석(Nonparametric Regression)은 선형회귀분석의 문제점을 극복할 수 있는 방법으로 변수간의 관계의 형태를 미리 가정하지 않고 데이터에 의해 결정하는 방법이다. 본 연구에서는 유전자 알고리즘을 비모수 회귀분석법 중의 하나인 Regressoin Splines에 적용하였다. 인위적 데이터를 이용한 평가 결과 유전자 알고리즘은 다양한 상황에서 매우 우수한 것으로 나타났다.

  • PDF

의료이용도에 대한 인구학적 변수의 효과분석의 방법 (Analysis of the Effects of Demographic Variables on Health Care Services Using the Spline Regression)

  • 김병익;이영조;권순호;한달선
    • 보건행정학회지
    • /
    • 제1권1호
    • /
    • pp.19-26
    • /
    • 1991
  • Demographic variables have a great deal of impact on the utilization of health services. In this paper, the use of segmented polinomials is shown to be superior to the simple use of dummy variables and simple polinomials in explaining differences in health care utilization with respect to sex and age differences.

  • PDF

서울의 온도 패턴 변화 (Change of temperature patterns in Seoul)

  • 장학진;주용성
    • Journal of the Korean Data and Information Science Society
    • /
    • 제20권1호
    • /
    • pp.89-96
    • /
    • 2009
  • 이 논문에서 우리는 1961년부터 2008년 사이의 서울지역 온도변화를 스펙트럴 이분산성 모델을 이용하여 연구하였다. 제안한 모델에서 평균 함수는 계절효과를 주기함수를 이용하여 설명하였고, 온도의 전체적인 상승을 이차 회귀 스플라인 곡선을 이용하여 설명하였다. 분산함수 또한 분산의 계절성을 설명하기 위하여 주기함수를 사용하였다. 우리는 연평균온도가 과거 48년 동안 약 1.5도 가량 증가했음을 알 수 있었다. 연평균온도의 상승은 겨울 온도가 상승하는 것에 기인하는 것이었고, 이는 연중 온도변화의 진폭이 줄어들게 만들었다.

  • PDF

B-spline polynomials models for analyzing growth patterns of Guzerat young bulls in field performance tests

  • Ricardo Costa Sousa;Fernando dos Santos Magaco;Daiane Cristina Becker Scalez;Jose Elivalto Guimaraes Campelo;Clelia Soares de Assis;Idalmo Garcia Pereira
    • Animal Bioscience
    • /
    • 제37권5호
    • /
    • pp.817-825
    • /
    • 2024
  • Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

Bayesian curve-fitting with radial basis functions under functional measurement error model

  • Hwang, Jinseub;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
    • /
    • 제26권3호
    • /
    • pp.749-754
    • /
    • 2015
  • This article presents Bayesian approach to regression splines with knots on a grid of equally spaced sample quantiles of the independent variables under functional measurement error model.We consider small area model by using penalized splines of non-linear pattern. Specifically, in a basis functions of the regression spline, we use radial basis functions. To fit the model and estimate parameters we suggest a hierarchical Bayesian framework using Markov Chain Monte Carlo methodology. Furthermore, we illustrate the method in an application data. We check the convergence by a potential scale reduction factor and we use the posterior predictive p-value and the mean logarithmic conditional predictive ordinate to compar models.

다원회귀(多元回歸) MODEL에 있어서 구조변화(構造變化)에 관한 연구(硏究) (A Study on Structural Change in the Multivariate Regression Model)

  • 조암
    • 품질경영학회지
    • /
    • 제13권1호
    • /
    • pp.20-25
    • /
    • 1985
  • There are several approaches for dealing with the structural change in regression model, but by introducing a concept of Spline, the structural change can be expressed more clearly. This makes it possible not only to know the location where the structural change happens and the total number, but also to derive posterior distribution from anterior-posterior distribution when the probability of the judgement anterior for entire combination was given to each model, by which, the model that has the highest posterior probability is the method which realizes the structural change. The purpose of this study is to find a peculiarity of the posterior probability on the occasion of anterior information acquired and of not acquired with Baysian approach.

  • PDF