• 제목/요약/키워드: K-S test statistics

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Spillover Effects of Foreign Direct Investment Inflows and Exchange Rates on the Banking Industry in China

  • Lee, Jung Wan;Wang, Zhen
    • The Journal of Asian Finance, Economics and Business
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    • 제5권2호
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    • pp.15-24
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    • 2018
  • The study examines the magnitude of economic spillover and the impact of foreign direct investment (FDI) inflows on the efficiency of the bank industry in China. This study employs unit root tests, cointegration tests and cointegrating regression analysis, including fully modified ordinary least squares (FMOLS), canonical cointegrating regression (CCR) and dynamic OLS (DOLS) to test the proposed hypotheses. The sample is restricted to the period of time in which monthly data is available and comparable among variables for the period from January 2002 to October 2013 (142 observations). All of the time series data was collected and retrieved from the People's Bank of China, China Monthly Statistics from the National Bureau of Statistics of China, and International Financial Statistics database from International Monetary Fund. The results of the Johansen cointegration test suggest that there is a long-run equilibrium relationship between FDI inflows, foreign exchange rate and banks performance in China. The results of cointegrating regression analysis using FMOLS, CCR and DOLS suggest that M2 supply and FDI inflows are significant at the 0.01 level. The results confirm that FDI inflows in the banking sector are positively related to the increase of banks productivity and performance and short-term loans in China. However, the results suggest that Chinese Yuan currency exchange rate to U.S. dollar is not significant in the banking and financial industry of China.

Mixed Replacement Designs for Life Testing with Interval Censoring

  • Tai Sup;kesar Singh
    • Communications for Statistical Applications and Methods
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    • 제6권2호
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    • pp.443-456
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    • 1999
  • The estimation of mean lifetimes in presence of interval censoring with mixed replacement procedure are examined when the distribution s of lifetimes are exponential. it is assumed that due to physical restrictions and/or economic constraints the number of failures is investigated only at several inspection times during the lifetime test; thus there is interval censoring. Comparisons of mixed replacement designs are made with those with and without replacement The maximum likelihood estimator is found in an implicit form. The Cramer-Rao lower bound which is the asymptotic variance of the estimator is derived. The test conditions for minimizing the Cramer-Rao lower bound and minimizing the test costs within a desired width of the Cramer-Rao bound have been studied.

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Efficiency Loss Due to Censoring for Testing against a Change-Point in Failure Rate

  • Yum, Junkeun;Kim, Daekyung
    • 품질경영학회지
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    • 제22권3호
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    • pp.119-123
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    • 1994
  • A frequently recurring question posed by researchers concerns a test of a constant failure rate against the alternative of a failure rate involving a single chang-point. Park (1988) has presented a new test procedure for testing constant failure rate against a bathtub shaped (upside-down bathtub shaped) failure rate. assuming that the proportion of population that fails at or before the change point of failure rate is known. Jeong (1992) has extended Park's test to randomly censored data under the same assumption. In this paper, we have investigated efficiency loss to the presence of censoring.

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Bayesian Hypothesis Testing in Multivariate Growth Curve Model.

  • Kim, Hea-Jung;Lee, Seung-Joo
    • Journal of the Korean Statistical Society
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    • 제25권1호
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    • pp.81-94
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    • 1996
  • This paper suggests a new criterion for testing the general linear hypothesis about coefficients in multivariate growth curve model. It is developed from a Bayesian point of view using the highest posterior density region methodology. Likelihood ratio test criterion(LRTC) by Khatri(1966) results as an approximate special case. It is shown that under the simple case of vague prior distribution for the multivariate normal parameters a LRTC-like criterion results; but the degrees of freedom are lower, so the suggested test criterion yields more conservative test than is warranted by the classical LRTC, a result analogous to that of Berger and Sellke(1987). Moreover, more general(non-vague) prior distributions will generate a richer class of tests than were previously available.

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Detection of Change-Points by Local Linear Regression Fit;

  • Kim, Jong Tae;Choi, Hyemi;Huh, Jib
    • Communications for Statistical Applications and Methods
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    • 제10권1호
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    • pp.31-38
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    • 2003
  • A simple method is proposed to detect the number of change points and test the location and size of multiple change points with jump discontinuities in an otherwise smooth regression model. The proposed estimators are based on a local linear regression fit by the comparison of left and right one-side kernel smoother. Our proposed methodology is explained and applied to real data and simulated data.

On a Subset Selection Procedure Based on Hodges-Lehmann Estimators

  • Song, Moon-Sup;Kim, Soon-Ock
    • Journal of the Korean Statistical Society
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    • 제16권1호
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    • pp.26-36
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    • 1987
  • In this paper, we study on a subset selection procedure based on Hodges-Lehmann estimators derived from the Wilcoxon test. To estimate the standard error of the Hodges-Lehmann estimators, the biweight A-estimator of scale is used. The Pitman efficiency of the proposed rule is compared with the Gupta's rule and the trimmed-means rule through a small-sample Monte Carlo study. The results show that the proposed rule satisfies the $P^*$-condition and is very efficient in various heavy-tailed distributions.

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Unbalanced ANOVA for Testing Shape Variability in Statistical Shape Analysis

  • Kim, Jong-Geon;Choi, Yong-Seok;Lee, Nae-Young
    • 응용통계연구
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    • 제23권2호
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    • pp.317-323
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    • 2010
  • Measures are very useful tools for comparing the shape variability in statistical shape analysis. For examples, the Procrustes statistic(PS) is isolated measure, and the mean Procrustes statistic(MPS) and the root mean square measure(RMS) are overall measures. But these measures are very subjective, complicated and moreover these measures are not statistical for comparing the shape variability. Therefore we need to study some tests. It is well known that the Hotelling's $T^2$ test is used for testing shape variability of two independent samples. And for testing shape variabilities of several independent samples, instead of the Hotelling's $T^2$ test, one way analysis of variance(ANOVA) can be applied. In fact, this one way ANOVA is based on the balanced samples of equal size which is called as BANOVA. However, If we have unbalanced samples with unequal size, we can not use BANOVA. Therefore we propose the unbalanced analysis of variance(UNBANOVA) for testing shape variabilities of several independent samples of unequal size.

대학 입학전형별 학업성취도 연구 (A Study on the Performance Evaluation of the College-Entrance Processes)

  • 오정현;정재윤;홍영훈;박상규;김삼용
    • 응용통계연구
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    • 제23권5호
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    • pp.987-996
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    • 2010
  • 대학 입학전형은 각 대학의 교육목적에 맞고 그 교육목표를 이룰 수 있는 적합한 인재상에 부합하는 학생들을 선발하는 것에 있다. 그리고 최근 입학사정관제의 도입으로 학생의 잠재력을 발굴하여 선발하는 전형을 정착시키려는 노력을 하고 있다. 이 점에서 과연 다양한 평가방식이 학생들의 질적 특성까지 반영하여 그들의 잠재력이 잘 평가되는지, 또 전형요소에 따라 계열, 모집단위 등의 특성에 맞는 학생들이 제대로 평가되고 있는지에 대하여 통계적 타당성을 검증할 필요성이 있다. 대학학업성취도를 바탕으로 하여 여러 요인들의 영향력을 통계적 방법으로 분석한다.

Testing Homogeneity of Diagonal Covariance Matrices of K Multivariate Normal Populations

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • 제6권3호
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    • pp.929-938
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    • 1999
  • We propose a criterion for testing homogeneity of diagonal covariance matrices of K multivariate normal populations. It is based on a factorization of usual likelihood ratio intended to propose and develop a criterion that makes use of properties of structures of the diagonal convariance matrices. The criterion then leads to a simple test as well as to an accurate asymptotic distribution of the test statistic via general result by Box (1949).

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유전자 발현 데이터에 대한 다중검정법 비교 및 분석 (Comparison and analysis of multiple testing methods for microarray gene expression data)

  • 서수민;김태훈;김재희
    • Journal of the Korean Data and Information Science Society
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    • 제25권5호
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    • pp.971-986
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    • 2014
  • 동시에 여러 개의 가설검정 수행시 귀무가설이 참일 경우 귀무가설을 기각할 확률이 커지는 문제가 발생한다. 이러한 다중검정 문제 해결을 위해 여러 연구에서는 가설검정시 필요한 집단별 오류율(FWER; family-wise error rate), 위발견율 (FDR; false discovery rate) 또는 위비발견율 (FNR; false nondiscovery rate) 과 통계량을 고려하여 검정력을 높이고자 하였다. 본 연구에서는 T 통계량, 수정된 T 통계량, 그리고 LPE (local pooled error) 통계량 기반 P값을 이용한 Bonferroni (1960) 방법, Holm (1979) 방법, Benjamini와 Hochberg (1995) 방법과 Benjamini와 Yekutieli (2001) 방법 그리고 Z 통계량 기반 Sun과 Cai (2007) 방법을 고찰하고 모의실험을 통해 다중검정 능력을 비교하였다. 또한 실제 데이터로 애기장대 유전자 발현 데이터에 대해 여러 가지 다중검정법을 통해 유의한 유전자들을 선별하였다.