• 제목/요약/키워드: Regression Test

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A Score test for Detection of Outliers in Nonlinear Regression

  • Kahng, Myung-Wook
    • Journal of the Korean Statistical Society
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    • 제22권2호
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    • pp.201-208
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    • 1993
  • Given the specific mean shift outlier model, the score test for multiple outliers in nonlinear regression is discussed as an alternative to the likelihood ratio test. The geometric interpretation of the score statistic is also presented.

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Testing Outliers in Nonlinear Regression

  • Kahng, Myung-Wook
    • Journal of the Korean Statistical Society
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    • 제24권2호
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    • pp.419-437
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    • 1995
  • Given the specific mean shift outlier model, several standard approaches to obtaining test statistic for outliers are discussed. Each of these is developed in detail for the nonlinear regression model, and each leads to an equivalent distribution. The geometric interpretations of the statistics and accuracy of linear approximation are also presented.

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Asymptotic Properties of Outlier Tests in Nonlinear Regression

  • Kahng, Myung-Wook
    • Journal of the Korean Data and Information Science Society
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    • 제17권1호
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    • pp.205-211
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    • 2006
  • For a linear regression model, the necessary and sufficient condition for the asymptotic consistency of the outlier test statistic is known. An analogous condition for the nonlinear regression model is considered in this paper.

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The General Linear Test in the Ridge Regression

  • Bae, Whasoo;Kim, Minji;Kim, Choongrak
    • Communications for Statistical Applications and Methods
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    • 제21권4호
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    • pp.297-307
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    • 2014
  • We derive a test statistic for the general linear test in the ridge regression model. The exact distribution for the test statistic is too difficult to derive; therefore, we suggest an approximate reference distribution. We use numerical studies to verify that the suggested distribution for the test statistic is appropriate. A asymptotic result for the test statistic also is considered.

통계해석에 의한 G/T 4톤급 연안어선의 유효마력 추정 (Prediction of Effective Horsepower for G/T 4 ton Class Coast Fishing Boat Using Statistical Analysis)

  • 박충환;심상목;조효제
    • 한국해양공학회지
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    • 제23권6호
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    • pp.71-76
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    • 2009
  • This paper describes a statistical analysis method for predicting a coast fishing boat's effective horsepower. The EHP estimation method for small coast fishing boats was developed, based on a statistical regression analysis of model test results in a circulating water channel. The statistical regression formula of a fishing boat's effective horsepower is determined from the regression analysis of the resistance test results for 15 actual coast fishing boats. This method was applied to the effective horsepower prediction of a G/T 4 ton class coast fishing boat. From the estimation of the effective horsepower using this regression formula and the experimental model test of the G/T 4 ton class coast fishing boat, the estimation accuracy was verified under 10 percent of the design speed. However, the effective horsepower prediction method for coast fishing boats using the regression formula will be used at the initial design and hull-form development stage.

여러개의 단순 선형 회귀모형에서 순차기울기를 이용한 평행성 검정 (Parallelism Test of Slope in a Several Simple Linear Regression Model based on a Sequential Slope)

  • 김주희;김동재
    • 응용통계연구
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    • 제26권6호
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    • pp.1009-1018
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    • 2013
  • 회귀분석은 변수들간의 관계를 파악하는데 유용하게 사용된다. 여러개의 모집단을 비교할 때, 여러 모집단이 갖는 각각의 회귀직선의 기울기가 같은지 검정하는 것이 필요할 때가 있다. 본 논문에서는 순차기울기를 추정한 후 ANOVA의 F-검정법과 Kruskal-Wallis (1952)검정법을 이용한 방법을 각각 제안하였다. 또한, 몬테카를로 모의시험 연구를 통해 본 논문에서 제안한 두 가지 방법과 Park과 Kim (2009)이 제안한 기존 방법의 검정력을 비교하였다.

On the Goodness-of-fit Test in Regression Using the Difference Between Nonparametric and Parametric Fits

  • Hong, Chang-Kon;Joo, Jae-Seon
    • Communications for Statistical Applications and Methods
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    • 제8권1호
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    • pp.1-14
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    • 2001
  • This paper discusses choosing the weight function of the Hardle and Mammen statistic in nonparametric goodness-of-fit test for regression curve. For this purpose, we modify the Hardle and Mammen statistic and derive its asymptotic distribution. Some results on the test statistic from the wild bootstrapped sample are also obtained. Through Monte Carlo experiment, we check the validity of these results. Finally, we study the powers of the test and compare with those of the Hardle and Mammen test through the simulation.

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The Identification Of Multiple Outliers

  • Park, Jin-Pyo
    • Journal of the Korean Data and Information Science Society
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    • 제11권2호
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    • pp.201-215
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    • 2000
  • The classical method for regression analysis is the least squares method. However, if the data contain significant outliers, the least squares estimator can be broken down by outliers. To remedy this problem, the robust methods are important complement to the least squares method. Robust methods down weighs or completely ignore the outliers. This is not always best because the outliers can contain some very important information about the population. If they can be detected, the outliers can be further inspected and appropriate action can be taken based on the results. In this paper, I propose a sequential outlier test to identify outliers. It is based on the nonrobust estimate and the robust estimate of scatter of a robust regression residuals and is applied in forward procedure, removing the most extreme data at each step, until the test fails to detect outliers. Unlike other forward procedures, the present one is unaffected by swamping or masking effects because the statistics is based on the robust regression residuals. I show the asymptotic distribution of the test statistics and apply the test to several real data and simulated data for the test to be shown to perform fairly well.

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단계별 비행훈련 성패 예측 모형의 성능 비교 연구 (Comparison of Classification Models for Sequential Flight Test Results)

  • 손소영;조용관;최성옥;김영준
    • 대한인간공학회지
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    • 제21권1호
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    • pp.1-14
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    • 2002
  • The main purpose of this paper is to present selection criteria for ROK Airforce pilot training candidates in order to save costs involved in sequential pilot training. We use classification models such Decision Tree, Logistic Regression and Neural Network based on aptitude test results of 288 ROK Air Force applicants in 1994-1996. Different models are compared in terms of classification accuracy, ROC and Lift-value. Neural network is evaluated as the best model for each sequential flight test result while Logistic regression model outperforms the rest of them for discriminating the last flight test result. Therefore we suggest a pilot selection criterion based on this logistic regression. Overall. we find that the factors such as Attention Sharing, Speed Tracking, Machine Comprehension and Instrument Reading Ability having significant effects on the flight results. We expect that the use of our criteria can increase the effectiveness of flight resources.

Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

  • Singh, Ajay;Singh, Avtar;Singh, Manvendra;Prakash, Ved;Ambhore, G.S.;Sahoo, S.K.;Dash, Soumya
    • Asian-Australasian Journal of Animal Sciences
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    • 제29권6호
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    • pp.775-781
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    • 2016
  • A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM) considering different order of Legendre polynomial for the additive genetic effect (4th order) and the permanent environmental effect (5th order). Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11) to 0.99 (TD-4 and TD-5). The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.