• Title/Summary/Keyword: quantiles

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Analysis on Meteorological Factors related to the Distribution of PM10 Concentration in Busan (부산지역 미세먼지 농도 분포에 따른 기상요소 분석)

  • Kim, Min-Kyoung;Jung, Woo-Sik;Lee, Hwa Woon;Do, Woo-Gon;Cho, Jung-Gu;Lee, Kwi-Ok
    • Journal of Environmental Science International
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    • v.22 no.9
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    • pp.1213-1226
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    • 2013
  • $PM_{10}$ concentration is related to the meteorological variables including to local and synoptic meteorology. In this study the $PM_{10}$ concentrations of Busan in 2007~2011 were analyzed and the days of yellow sand or rainfall which is more than 5 mm were excluded. The sections of $PM_{10}$ concentration were divided according to 10-quantiles, quartiles and 90-quantiles. The 90-quantiles of daily $PM_{10}$ concentration were selected as high concentration dates. In the high concentration dates the daily mean averaged cloudness, mean daily surface wind speed, daily mean surface pressure and PBL height were low and diurnal variation of surface pressure and daily maximum surface temperature were high. When the high $PM_{10}$ dates occurred, the west and south wind blew on the ground and the west wind blew strongly on the 850 hPa. So it seemed that long range transboundary air pollutants made effects on the high concentration dates. The cluster analysis using Hysplit model which is the backward trajectory was made on the high concentration dates. As a result, 3 clusters were extracted and on the short range transboundary cluster the daily mean relative humidity and cloudness were high and PBL height was low.

Analysis of Precipitation Distribution in the region of Gangwon with Spatial Analysis (II): Analysis of Quantiles with Interested Durations and Return Periods (공간분석을 이용한 강원도 지역의 강수분포 분석 (II): 지속기간 및 재현기간별 확률강수량 분석)

  • Jeong, Chang-Sam;Um, Myoung-Jin;Heo, Jun-Haeng
    • Journal of the Korean Society of Hazard Mitigation
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    • v.9 no.6
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    • pp.99-109
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    • 2009
  • In this study, often the spatial distribution of precipitation was analyzed using the quantile with regional frequency analysis and spatial analysis to find out the detail distribution of extreme precipitation for preventing the disaster in the region of Gangwon. The hourly precipitation data of 66 stations in Gangwon were used. As the results of regional frequency analysis, it shows that the generalized logistic (GLO) distribution is the best for the region of Gangwon. As the results of spatial analysis, the quaniles have high vaules nearby Seolakdong, Daegwallyeong and Cheongil as the duration of precipitation increase, and the change of spatial distribution occurs severely according to the duration of precipitation. The spatial characteristics of precipitation appears clearly as the return period of quantile increases. As the results of the spatial distribution of precipitation in Gangwon heavy quantiles usually are appeared in Yongdong, and the spatial distributions of quantile in Yongseo are various according to the duration and the return period of quantile. Therefore, to estimate more accurate quantiles in Gangwon, various geographical and weather conditions are considered additionally for the regional precipitation frequency analysis.

A new method for calculating quantiles of grouped data based on the frequency polygon (집단화된 통계자료의 도수다각형에 근거한 새로운 분위수 계산법)

  • Kim, Hyuk Joo
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.383-393
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    • 2017
  • When we deal with grouped statistical data, it is desirable to use a calculation method that gives as close value to the true value of a statistic as possible. In this paper, we suggested a new method to calculate the quantiles of grouped data. The main idea of the suggested method is calculating the data values by partitioning the pentagons, that correspond to the class intervals in the frequency polygon drawn according to the histogram, into parts with equal area. We compared this method with existing methods through simulations using some datasets from introductory statistics textbooks. In the simulation study, we simulated as many data values as given in each class interval using the inverse transform method, on the basis of the distribution that has the shape given by the frequency polygon. Using the sum of squares of differences from quantiles of the simulated data as a criterion, the suggested method was found to have better performance than existing methods for almost all quartiles and deciles.

A Comparative Study on Lowflow Quantiles Estimation in Han River Basin (한강유역의 확률갈수량 추정기법 비교연구)

  • Kim, Kyung-Duk;Kim, Don-Soo;Heo, Jun-Haeng;Kim, Kyu-Ho
    • Journal of Korea Water Resources Association
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    • v.36 no.2
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    • pp.315-324
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    • 2003
  • Stream flow data was analyzed for determining the lowflow which is the standard for river maintenance flow. Lowflow quantiles were estimated based on the parametric and nonparametric methods and two methods were compared by Monte Carlo simulation study. As the results of the parametric method, three probability distributions such as gamma-2, lognormal-2 and Weibull-2, are selected as appropriate models for stream flow data of 13 stations in Han River Basins. According to simulation results, relative bias (RBIAS) and relative root mean square error (RRMSE) of the lowflow quantiles are the smallest when the applied and population models are the same. The fame statistical properties from the nonparametric models are good within the interpolation range. Among 7 bandwidth selectors used in this study, the RRMSEs of the Park and Marron method (PM) are the smallest while those of the Shoaler and Jones method (SJ) are the largest.

Inbreeding affected differently on observations distribution of a growth trait in Iranian Baluchi sheep

  • Binabaj, Fateme Bahri;Farhangfar, Seyyed Homayoun;Jafari, Majid
    • Animal Bioscience
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    • v.34 no.4
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    • pp.506-515
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    • 2021
  • Objective: Initial consequence of inbreeding is inbreeding depression which impairs the performance of growth, production, health, fertility and survival traits in different animal breeds and populations. The effect of inbreeding on economically important traits should be accurately estimated. The effect of inbreeding depression on growth traits in sheep has been reported in many breeds. Based on this, the main objective of the present research was to evaluate the impact of inbreeding on some growth traits of Iranian Baluchi sheep breed using quantile regression model. Methods: Pedigree and growth traits records of 13,633 Baluchi lambs born from year 1989 to 2016 were used in this research. The traits were birth weight, weaning weight, six-month weight, nine-month weight, and yearling weight. The contribution, inbreeding and co-ancestry software was used to calculate the pedigree statistics and inbreeding coefficients. To evaluate the impact of inbreeding on different quantiles of each growth trait, a series of quantile regression models were fitted using QUANTREG procedure of SAS software. Annual trend of inbreeding was also estimated fitting a simple linear regression of lamb's inbreeding coefficient on the birth year. Results: Average inbreeding coefficient of the population was 1.63 percent. Annual increase rate of inbreeding of the flock was 0.11 percent (p<0.01). The results showed that the effect of inbreeding in different quantiles of growth traits is not similar. Also, inbreeding affected differently on growth traits, considering lambs' sex and type of birth. Conclusion: Quantile regression revealed that inbreeding did not have similar effect on different quantiles of growth traits in Iranian Baluchi lambs indicating that at a given age and inbreeding coefficient, lambs with different sex and birth type were not equally influenced by inbreeding.

Rainfall Quantile Estimation Using Scaling Property in Korea (스케일 성질을 이용한 확률강우량의 추정)

  • Jung, Young-Hun;Kim, Soo-Young;Kim, Tae-Soon;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.41 no.9
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    • pp.873-884
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    • 2008
  • In this study, rainfall quantile was estimated using scale invariance property of rainfall data with different durations and the applicability of such property was evaluated for the rainfall data of South Korea. For this purpose, maximum annual rainfall at 22 recording sites of Korea Meteorological Administration (KMA) having relatively long records were used to compare rainfall quantiles between at-site frequency analysis and scale invariance property. As the results, the absolute relative errors of rainfall quantiles between two methods show at most 10 % for hourly rainfall data. The estimated quantiles by scale invariance property can be generally applied in the 8 of 14 return periods used in this study. As an example of down-scaling method, rainfall quantiles of $10{\sim}50$ minutes duration were estimated by scale invariance property based on index duration of 1 hour. These results show less than 10 % of absolute relative errors except 10 minutes duration. It is found that scale invariance property can be applied to estimate rainfall quantile for unmeasured rainfall durations.

Matching Conditions for Predicting the Random Effects in ANOVA Models

  • Chang, In-Hong
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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    • pp.1-6
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    • 2006
  • We consider the issue of Bayesian prediction of the unobservable random effects, And we characterize priors that ensure approximate frequentist validity of posterior quantiles of unobservable random effects. Finally we show that the probability matching criteria for prediction of unobservable random effects in one-way random ANOVA model.

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