• Title/Summary/Keyword: Grubbs-type statistics

Search Result 2, Processing Time 0.019 seconds

Detecting Multiple Outliers Using the Gaps of Order Statistics

  • Kim, Hyun Chul
    • Communications for Statistical Applications and Methods
    • /
    • v.2 no.2
    • /
    • pp.184-197
    • /
    • 1995
  • An objective and one-step detection procedure of multiple outliers is suggested by using the gaps of the order statistics. The detection procedure can be used as a routine outlier detection method of a statistical analysis computer program. The procedure is applied to some examples including the data selected by Kitagawa.

  • PDF

Estimating design floods for ungauged basins in the geum-river basin through regional flood frequency analysis using L-moments method (L-모멘트법을 이용한 지역홍수빈도분석을 통한 금강유역 미계측 유역의 설계홍수량 산정)

  • Lee, Jin-Young;Park, Dong-Hyeok;Shin, Ji-Yae;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
    • /
    • v.49 no.8
    • /
    • pp.645-656
    • /
    • 2016
  • The study performed a regional flood frequency analysis and proposed a regression equation to estimate design floods corresponding to return periods for ungauged basins in Geum-river basin. Five preliminary tests were employed to investigate hydrological independence and homogeneity of streamflow data, i.e. the lag-one autocorrelation test, time homogeneity test, Grubbs-Beck outlier test, discordancy measure test ($D_i$), and regional homogeneity measure (H). The test results showed that streamflow data were time-independent, discordant and homogeneous within the basin. Using five probability distributions (generalized extreme value (GEV), three-parameter log-normal (LN-III), Pearson type 3 (P-III), generalized logistic (GLO), generalized Pareto (GPA)), comparative regional flood frequency analyses were carried out for the region. Based on the L-moment ratio diagram, average weighted distance (AWD) and goodness-of-fit statistics ($Z^{DIST}$), the GLO distribution was selected as the best fit model for Geum-river basin. Using the GLO, a regression equation was developed for estimating regional design floods, and validated by comparing the estimated and observed streamflows at the Ganggyeong station.