• 제목/요약/키워드: Normality

검색결과 720건 처리시간 0.023초

A comparison of tests for homoscedasticity using simulation and empirical data

  • Anastasios Katsileros;Nikolaos Antonetsis;Paschalis Mouzaidis;Eleni Tani;Penelope J. Bebeli;Alex Karagrigoriou
    • Communications for Statistical Applications and Methods
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    • 제31권1호
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    • pp.1-35
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    • 2024
  • The assumption of homoscedasticity is one of the most crucial assumptions for many parametric tests used in the biological sciences. The aim of this paper is to compare the empirical probability of type I error and the power of ten parametric and two non-parametric tests for homoscedasticity with simulations under different types of distributions, number of groups, number of samples per group, variance ratio and significance levels, as well as through empirical data from an agricultural experiment. According to the findings of the simulation study, when there is no violation of the assumption of normality and the groups have equal variances and equal number of samples, the Bhandary-Dai, Cochran's C, Hartley's Fmax, Levene (trimmed mean) and Bartlett tests are considered robust. The Levene (absolute and square deviations) tests show a high probability of type I error in a small number of samples, which increases as the number of groups rises. When data groups display a nonnormal distribution, researchers should utilize the Levene (trimmed mean), O'Brien and Brown-Forsythe tests. On the other hand, if the assumption of normality is not violated but diagnostic plots indicate unequal variances between groups, researchers are advised to use the Bartlett, Z-variance, Bhandary-Dai and Levene (trimmed mean) tests. Assessing the tests being considered, the test that stands out as the most well-rounded choice is the Levene's test (trimmed mean), which provides satisfactory type I error control and relatively high power. According to the findings of the study and for the scenarios considered, the two non-parametric tests are not recommended. In conclusion, it is suggested to initially check for normality and consider the number of samples per group before choosing the most appropriate test for homoscedasticity.

가능도 함수를 기초로 한 다변량 정규성 검정 (A Test of the Multivariate Normality Based on Likelihood Functions)

  • 여인권
    • 응용통계연구
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    • 제15권2호
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    • pp.223-232
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    • 2002
  • 이 논문에서는 비선형 변환과 가능도 함수를 이용하여 다변량 자료의 정규성을 검정하는 방법에 대해 알아본다. 사용된 변환은 변환모수에 따라 여러 가지 형태를 가지는 변환족을 구성하는데 이 변환모수를 검정하여 자료의 정규성을 검정한다. 모수의 검정은 점수함수(score function)을 기초로 이루어지며 표본크기가 적은 경우에도 검정통계량의 분포를 유도하기 위한 모수적 붓스트랩 검정방법이 사용된다. 모의실험 결과 기존의 방법과 검정력을 비교하여 제안된 방법이 검정력이 높은 것으로 나타났다.

주행거리별 운행차 배출가스 분포 추정 모델에 관한 연구 (A Study on the Inference Model of In-use Vehicles Emission Distribution according to the Vehicle Mileage)

  • 김현우
    • 한국자동차공학회논문집
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    • 제10권4호
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    • pp.85-92
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    • 2002
  • To investigate the safety of the in-use vehicles emission against the tail-pipe emission regulation, in-use vehicles emission trend according to vehicle mileage should be known. But it is impossible to collect all vehicles emission data In order to know that. Therefore, it is necessary to establish a statistically meaningful inference method that can be used generally to estimate in-use vehicles emissions distribution according to the vehicle mileage with relatively less in-use vehicles emission data. To do this, a linear regression model that solved the problems of data normality and common variance of error was studied. As a way that can secure the data normality, In(emission) instead of emission itself was used as a sampled data. And a reciprocal of mileage was suggested as a factor to secure common variance of error. As an example, 36 data of FTP-75 test were handled in this study. As a result, using average value and standard deviation at each mileage which were inferred from a linear regression model, probability density distribution and cumulative distribution of emissions according to the vehicle mileage were obtained and it was possible to predict the deterioration factor through full useful life mileage and also possible to decide whether those in-use vehicles will meet the tail-pipe emission regulations or not.

1세포기 생쥐 수정란의 초급속동결; 적정 탈수시간과 복수시간 (Ultrarapid-freezing of 1 Ceil Mouse Embryos; Optimal Times of Rehydration and Dehydration)

  • 박영식;전상식
    • 한국수정란이식학회지
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    • 제11권1호
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    • pp.27-33
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    • 1996
  • The efficient cryopreservation of embryos requires optimal times of dehydration and rehydration This study was carried out to investigate the effect of various times of dehydration and rehydration The effects were evaluated through testing morphological normality and developmental ability of 1 cell mouse embryos which were ultrarapidly frozen and thawed. The 1 cell embryos were dehydrated for 1.5, 3, 5, and 10 minutes using mPBS-BSA containing 3.SM DMSO and 0.25M sucrose on cooling chamber or on ice. After ultrarapidly frozen and thawed, they were rehydrated for 0, 0.5 and 5 minutes with mPBS-BSA containing 0.25M sucrose at room temperature. The results obtained were as follows: The embryos that were rehydrated for 0.5 minutes showed higher normality than the embryos for 0 and 5 minutes did. The embryos that were dehydrated for 10 minutes showed higher normality than the embryos for 1.5, 3, and 5 minutes did. The developmental ability of normal thawed-embryos was high in 10 minute dehydration treatment compared to other treatments. However, it was not affected by cooling methods (on ice and on cooling chamber) for embryo dehydration.

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A Goodness-of-Fit Test for Multivariate Normal Distribution Using Modified Squared Distance

  • Yim, Mi-Hong;Park, Hyun-Jung;Kim, Joo-Han
    • Communications for Statistical Applications and Methods
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    • 제19권4호
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    • pp.607-617
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    • 2012
  • The goodness-of-fit test for multivariate normal distribution is important because most multivariate statistical methods are based on the assumption of multivariate normality. We propose goodness-of-fit test statistics for multivariate normality based on the modified squared distance. The empirical percentage points of the null distribution of the proposed statistics are presented via numerical simulations. We compare performance of several test statistics through a Monte Carlo simulation.

Simultaneous Tests with Combining Functions under Normality

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • 제22권6호
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    • pp.639-646
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    • 2015
  • We propose simultaneous tests for mean and variance under the normality assumption. After formulating the null hypothesis and its alternative, we construct test statistics based on the individual p-values for the partial tests with combining functions and derive the null distributions for the combining functions. We then illustrate our procedure with industrial data and compare the efficiency among the combining functions with individual partial ones by obtaining empirical powers through a simulation study. A discussion then follows on the intersection-union test with a combining function and simultaneous confidence region as a simultaneous inference; in addition, we discuss weighted functions and applications to the statistical quality control. Finally we comment on nonparametric simultaneous tests.

A General Class of Acceptance-Rejection Distributions and Its Applications

  • 김혜중;염준근;이영섭;조천호;정효상
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2003년도 추계학술대회
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    • pp.19-30
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    • 2003
  • In this paper we present a new family of distributions that allows a continuous variation not only from normality to non-normality but also from unimodality to bimodality. Its properties are especially useful in studying and making inferences about models involving the univariate truncated normal distribution. The properties of the family and its applications are given.

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비만환자와 정상인의 상.하지 수분분포 및 근육둘레 비교연구 (Study on Water Distribution and Muscle Circumference of Arm, Leg and Trunk of Between Obese Patient and Normality)

  • 차윤엽
    • 동의생리병리학회지
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    • 제19권1호
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    • pp.289-293
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    • 2005
  • The aim of this study was to investigate the importance of behavior habit and body exercise. We divided 164 volunteers into 2 groups. 82 volunteers was obese group($BMI{\geqq}25$), and the others was normal group(BMI<25). And we investigated the difference of water distribution and muscle circumference of arm, leg and trunk of between obese patient and normality. The results are as follows; Normal group was significantly higher than obese group in leg water distribution and muscle circumference rate as compared with arm(P<0.001). Normal group was significantly higher than obese group in leg water distribution and muscle circumference rate as compared with trunk(P<0.001). Each of the relation of water distribution and muscle circumference was significantly correlated with Pearson correlation analysis(r = 0.96, r = 0.6). In conclusion, there is very important that Low limb exercise and behavior habit in obese.