• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.663-676
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• 1997

We obtain the simultaneous unit roots test statistics for both regular and seasonal unit roots in a time series with possible seasonal deterministic trends. The limiting distributions of the proposed test statistics are derived and empirical percentiles of the test statistics are tabulated for some seasonal periods. The power and size of the test statistics are examined for finite samples through a Monte Carlo simulation and Compared with those of the Lagrange multiplier test.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.101-114
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• 1995

In this paper we consider the multiple unit root tests both for the regular and seasonal unit roots based on the Lagrange Multiplier(LM) principle. Unlike Li(1991)'s method, by plugging the restricted maximum likelihood estimates of the nuisance parameters in the model, we propose a Lagrange multiplier test which does not depend on the existence of the nuisance parameters. The asymptotic distribution of the proposed statistic is derived and empirical percentiles of the test statistic for selected seasonal periods are provided. The power and size of the test statistic for examined for finite samples through a Monte Carlo simularion.

• Atmosphere
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• v.24 no.3
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• pp.379-390
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• 2014

This study explores the long-term trends of surface air temperatures in 11 KMA stations over the period of 1960~2012. Both linear and nonlinear trends are examined for the $95^{th}$, $50^{th}$, and $5^{th}$ percentiles of daily maximum ($T_{max}$) and minimum temperatures ($T_{min}$) by using quantile regression method. It is found that in most stations linear trends of $T_{max}$ and $T_{min}$ are generally stronger in winter than in summer, and warming trend of the $5^{th}$ percentile temperature (cold extreme) is stronger than that of the $95^{th}$ percentile temperature (warm extreme) in both seasons. The nonlinear trends, which are evaluated by the second order polynomial fitting, show a strong nonlinearity in winter. Specifically, winter temperatures have increased until 2000s but slightly decreased afterward in all percentiles. This contrasts with the $95^{th}$ and $50^{th}$ percentiles of summer $T_{min}$ that show a decreasing trend until 1980s then an increasing trend. While this result is consistent with a seasonal dependence of the recent global warming hiatus, most of the nonlinear trends are statistically insignificant, making a quantitative attribution of nonlinear temperature trends challenging.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.4
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• pp.253-264
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• 2002

Surface ozone concentrations measured at 40 monitoring sites in three major cities (Seoul, Busan, and Daegu) of Korea during 1993~2000 were analyzed to understand the characteristics of temporal and spatial distributions. Trends were analyzed for annual mean, 95th percentiles of daily 8-hour maximum and days exceeding 8-h ozone standard of 60 ppb. Three indicators exhibited increasing trends (+0.75 ppb yr$^{-1}$ , +2.20 ppb yr$_{-1}$ , and +5.35 days yr$_{-1}$ on average) throughout the study period at all cities. Diurnal and seasonal variations were the largest in Seoul followed by Daegue and Busan, due to the high photochemical production and titration of ozone (Seoul), strong wind and constant supply of background ozone from the ocean (Busan). In the urban centers and industrial areas at all cities, scavenging of ozone by NO reduces the daily 8-hour maximum ozone by 10 ppb on average. High concentrations of ozone have frequently occurred in downwind eastern (Seoul and Daegu) or northern (Busan) sides of the territory. In particular, the coastal area of Busan had relatively high ozone level due to the local sea land breeze circulation. The results indicated that the temporal and spatial variations of ozone concentration were non -uniform and were closely related to the local environments; emission levels, climates, and geographic locations.

• Journal of Bio-Environment Control
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• v.27 no.3
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• pp.269-275
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• 2018

In order to establish the criterion for analyzing outdoor weather conditions in the greenhouse heating and cooling system design, we analyzed heating and cooling design outdoor temperatures by the annual percentile method and compared with design outdoor temperatures by the existing seasonal percentile method. In the annual percentile method, 0.4%, 1% and 2% of the total 8,760 hours per year are presented as cooling design outdoor temperatures and 99.6% and 99% as heating design outdoor temperatures. When the annual percentile method was adopted, heating design outdoor temperatures increased by 6.7 to 9.6% compared with the seasonal percentile method, and cooling design outdoor temperatures decreased by 0.6 to 1.1%. The maximum heating load in the same greenhouse condition decreased by 3.0 to 3.6% when the annual percentile method was adopted, but the effect on the maximum cooling load was insignificant. Therefore, it is necessary to consider the change of heating design outdoor temperatures to the annual percentile method, but it is not necessary to change the cooling design outdoor temperatures since there is little difference between the two methods.