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Ng, Chi Tim,Ko, Jonghan,Yeom, Jong-min,Jeong, Seungtaek,Jeong, Gwanyong,Choi, Myungin The Korean Society of Remote Sensing 2019 大韓遠隔探査學會誌 Vol.35 No.1
Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.
Chi Tim Ng,Jonghan Ko,Jong-Min Yeom,Seungtaek Jeong,Gwanyong Jeong,Myungin Choi 대한원격탐사학회 2019 大韓遠隔探査學會誌 Vol.35 No.1
Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.
Empirical likelihood method for longitudinal data generated from unequally-spaced Lèvy processes
박진경,Chi Tim Ng,나명환 한국통계학회 2020 Journal of the Korean Statistical Society Vol.49 No.3
By introducing the notion of “empirical likelihood function of observing sums”, unequally-spaced time series data and longitudinal data generated from Lévy processes can be analyzed. Characteristic function is further incorporated to handle the situations where the density function of the increments is difficult to obtain. In the situations where both characteristic function and the density function are available, it is shown through the simulation examples that the proposed empirical maximum likelihood method does not suffer from significant information loss comparing to the maximum likelihood estimation method. The performances of the proposed method is tested for both equally-spaced and unequally-spaced observations.
A New Integral Representation of the Coverage Probability of a Random Convex Hull
Son, Won,Ng, Chi Tim,Lim, Johan The Korean Statistical Society 2015 Communications for statistical applications and me Vol.22 No.1
In this paper, the probability that a given point is covered by a random convex hull generated by independent and identically-distributed random points in a plane is studied. It is shown that such probability can be expressed in terms of an integral that can be approximated numerically by function-evaluations over the grid-points in a 2-dimensional space. The new integral representation allows such probability be computed efficiently. The computational burdens under the proposed integral representation and those in the existing literature are compared. The proposed method is illustrated through numerical examples where the random points are drawn from (i) uniform distribution over a square and (ii) bivariate normal distribution over the two-dimensional Euclidean space. The applications of the proposed method in statistics are are discussed.
Computational explosion in the frequency estimation of sinusoidal data
Zhang, Kaimeng,Ng, Chi Tim,Na, Myunghwan The Korean Statistical Society 2018 Communications for statistical applications and me Vol.25 No.4
This paper highlights the computational explosion issues in the autoregressive moving average approach of frequency estimation of sinusoidal data with a large sample size. A new algorithm is proposed to circumvent the computational explosion difficulty in the conditional least-square estimation method. Notice that sinusoidal pattern can be generated by a non-invertible non-stationary autoregressive moving average (ARMA) model. The computational explosion is shown to be closely related to the non-invertibility of the equivalent ARMA model. Simulation studies illustrate the computational explosion phenomenon and show that the proposed algorithm can efficiently overcome computational explosion difficulty. Real data example of sunspot number is provided to illustrate the application of the proposed algorithm to the time series data exhibiting sinusoidal pattern.
A new active zero set descent algorithm for least absolute deviation with generalized LASSO penalty
Shi Yue,Ng Chi Tim 한국통계학회 2023 Journal of the Korean Statistical Society Vol.52 No.1
A new active zero set descent algorithm is proposed for least absolute deviation (LAD) problems with generalized LASSO penalty. Zero set contains the terms in the cost function that are zero-valued at the solution. Unlike state-of-art numerical approximation strategies such as interior point method, user-chosen threshold value is not required by the proposed algorithm to identify the zero set. Moreover, no nested iteration is needed. The algorithm updates the zero set and basis search directions recursively until optimality conditions are satisfied. It is also shown that the proposed algorithm converges in finitely many steps. Extensive simulation studies and real data analysis are conducted to confirm the time-efficiency of our algorithm.
Removing the singularity of a penalty via thresholding function matching
Van Cuong Nguyen,Chi Tim Ng 한국통계학회 2019 Journal of the Korean Statistical Society Vol.48 No.4
By introducing the idea of thresholding function matching, it is illustrated that both bridge penalty and log penalty can be transformed so as to circumvent certain difficulties in numerical computation and the definition of local minimality. The fact that both bridge penalty and log penalty have derivatives going to infinity at zero. This hinders their applications in statistics although it is reported in the literature that they allow recovery of sparse structure in the data under some conditions. It is illustrated in the simulation studies that in the variable selection problems, penalized likelihood estimation based on the transformed penalty obtained by the proposed thresholding function matching method outperform those based on many other state-of-art penalties, particularly when the covariates are strongly correlated. The one-to-one correspondence between the transformed penalties and their thresholding functions are also established.
Hypothesis testing via a penalized-likelihood approach
Nong, Quynh Van,Ng, Chi Tim,Lee, Woojoo,Lee, Youngjo Elsevier 2019 Journal of the Korean Statistical Society Vol.48 No.2
<P><B>Abstract</B></P> <P>It is illustrated in this paper that hypothesis testing procedures can be derived based on the penalized likelihood approach. Based on this point of view, many traditional hypothesis tests, including the two-sample mean test, score test, and Hotelling’s <SUP> T 2 </SUP> test are revisited under the penalized likelihood framework. Similar framework is also applicable to the empirical likelihood.</P>