• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.173-182
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• 1994

By applying slope estimator under the arbitrary error distributions proposed by Han(1993), if we define regression quantiles to give upper and lower trimming part and blocks of data, we show the proposed slope estimator has asymptotically efficient slope estimator when the number of regression quantiles to from blocks of data goes to sufficiently large.

• The Korean Journal of Applied Statistics
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• v.6 no.1
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• pp.79-93
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• 1993

We consider adaptive L-estimation of estimating slope parameter in regression model. The proposed estimator is simple extension of trimmed least squares estimator proposed by ruppert and carroll. The efficiency of the proposed estimator is especially well compared with usual least squares estimator, least absolute value estimator, and M-estimators designed for asymmetric distributions under asymmetric error distributions.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.15-27
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• 2001

One proposal is made for constructing nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of idea of Johns for estimating the center of the symmetric distribution together with the idea of regression quantiles and regression trimmed mean. This nonparametric estimator and some other L-estimators are studied by Monte Carlo.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.793-802
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• 2012

One proposal is made to construct a nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of the idea of minimizing approximate variance of a proposed estimator using regression quantiles. This nonparametric estimator and some other L-estimators are studied and compared with well known M-estimators through a simulation study.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.374-381
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• 2016

The sealing technique is widely used for repairing the cracks on the surface of concrete and preventing their expansion in the future. However, it is difficult to ensure the safety of the workers when sealing large structures in inconvenient working environments. This paper presents the development of a sealing robot system to seal various shapes of concrete surface in rough conditions for a long time. If the robot can maintain the desired contact force, the cracks can be completely sealed. An impedance force tracking controller with slope estimator is proposed to calculate the surface slope in real time using the robot position. It predicts the next point in order to prevent the robot from disengaging from the contact surface owing to quick slope changes. The proposed method has been verified by experimental results.

• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.179-187
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• 2016

The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

• Korean Journal of Ecology and Environment
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• v.48 no.2
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• pp.95-107
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• 2015

In order to identify long-term trends of water quality parameters in Lake Kyeongpo, Mann-Kendall test, Sen's slope estimator and linear regression were applied on data, with 15 parameters from three different sites and rainfall, monitored once in every two months from March to November during 1998~2013. Seasonal variation analysis only used Mann-Kendall test and Sen's slope estimator. Analysis result showed that salinity, transparency and nutrient variables (total phosphorus, dissolved inorganic phosphorus, total nitrogen, nitrate nitrogen, ammonia nitrogen) were only parameters having statistically significant trend. In linear regression analysis, salinity (surface and bottom layer of all sites) and transparency (only at site 1), were figured out with statistically significant increasing trend, while in non-parametric statistical method, salinity and transparency in all sites (surface, middle, deep) were figured out with statistically significant increasing trend. Water quality parameters showing statistically significant decreasing trends were dissolved oxygen (surface layer of site 1 and bottom layer of sites 2 and 3), total phosphorus (sites 1 and 2), dissolved inorganic phosphorus, total nitrogen, nitrate nitrogen and ammonia nitrogen in the linear regression analysis and, dissolved oxygen (bottom layer of all sites), total phosphorus, dissolved inorganic phosphorus, total nitrogen, nitrate nitrogen and ammonia nitrogen in the non-parametric method. Seasonal trend analysis result showed that salinity, turbidity, transparency and suspended solids in spring, salinity, transparency, nitrate nitrogen and suspended solids in summer and temperature, salinity, transparency and suspended solids in fall were the variables depending on the season with increasing trends. In general, rainfall during the research period showed decreasing trend. The significant reduction trends of nutrients in Lake Kyeongpo were believed to be related to lagoon restoration and water management project run by Gangneung city and under-water wear removal, but further detailed studies are needed to know the exact causes.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1009-1018
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• 2013

Regression analysis is useful to understand the relationship of variables; however, we need to test if the slope of each regression lines is the same when comparing several populations. This paper suggests a new parallelism test for several linear regression lines. We use F-test of ANOVA and Kruskal-Wallis (1952) tests after obtaining slope estimator from a sequential slope. In addition, a Monte Carlo simulation study is adapted to compare the power of the proposed methods with those of Park and Kim (2009).

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.163-175
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• 1998

The change of hazard rates at some unknown time point has been the interest of many statisticians. But it was restricted to the constant hazard rates which correspond to the exponential distribution. In this paper we generalize the change-point model in which any specific functional forms of hazard rates are net assumed. The assumed model includes various types of changes before and after the unknown time point. The Nelson estimator of cumulative hazard function is introduced. We estimate the change-point maximizing slope changes of Nelson estimator. Consistency and asymptotic distribution of bootstrap estimator are obtained using the martingale theory. Through a Monte Carlo study we check the performance of the proposed method. We also explain the proposed method using the Stanford Heart Transplant Data set.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.83-94
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• 2022

In order to actively prepare to frost damage that occurs in the process of growing crops, the spatial and temporal distribution of frost occurrence in South Korea was derived using frost observation data from 20 regions over the past 21 years (2000~2020). The main products are the number of frost days, first frost day, and last frost day by region. And the climatic trends of these results were identified by performing the Mann-Kendall trend test and Sen's slope estimator. In South Korea, a lot of frost occurs in the inland area to the west of the Taebaek and Sobaek Mountains. Relatively closer to the coastal area, the number of frost days is small, the first frost day is slow, and the last frost day is early. The east coast region has fewer frost days, the first frost day is later, and the last frost day is earlier than the west coast region. The southern sea, the southeastern sea region, and the island region rarely experience frost. As a result of the annual time series trend analysis, although South Korea is a country where climate warming is progressing, there was no trend in reducing the number of frost days and slowing the first frost day, and it was found that the last frost day is delayed by 0.5 days per year.