• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.1-13
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• 2017

This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

• Journal of The Korean Astronomical Society
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• v.42 no.2
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• pp.17-26
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• 2009

We estimate the enclosed mass profile in the central 10 pc of the Milky Way by analyzing the infrared photometry and the velocity observations of dynamically relaxed stellar population in the Galactic center. HST/NICMOS and Gemini Adaptive Optics images in the archive are used to obtain the number density profile, and proper motion and radial velocity data were compiled from the literature to find the velocity dispersion profile assuming a spherical symmetry and velocity isotropy. From these data, we calculate the the enclosed mass and density profiles in the central 10 pc of the Galaxy using the Jeans equation. Our improved estimates can better describe the exact evolution of the molecular clouds and star clusters falling down to the Galactic center, and constrain the star formation history of the inner part of the Galaxy.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.298-303
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• 2003

The eccentric rotor system has various problems by vibration of unbalance mass. Specially, it is difficult to analyze vibration problem for the drum washing machine due to correlation of transmission paths. We analyze the mechanical structure by multidimensional spectral density to identify the maximum vibration magnitude at the frequency domain. It estimates the coherence function of the signals to pass the transmission paths. In case of the drum washing machine, because the transmission paths are correlated partially it needs to determinate the priority ranking. And the correlated parts are eliminated using conditioned spectral density function. Finally the shielding effect method confirms the reasonability of the modeling.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.9-19
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• 1994

Beta-binomial model, which is reparametrized in terms of the mean probability $\mu$ of a positive deagnosis and the $\kappa$ of agreement, is widely used in psychology. When $\mu$ is close to 0, inference about $\kappa$ become difficult because likelihood function becomes constant. We consider Bayesian approach in this case. To apply Bayesian analysis, Gibbs sampler is used to overcome difficulties in integration. Marginal posterior density functions are estimated and Bayesian estimates are derived by using Gibbs sampler and compare the results with the one obtained by using numerical integration.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.517-529
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• 2016

This study compares the inverse transform and the composition methods for generating data from the Lindley distribution. The expression for the inverse of the distribution function for the Lindley distribution does not exist in closed form. Hence, authors of many empirical studies on the Lindley distribution used methods for generating Lindley variates other than the inverse transform. We generated data from the Lindley distribution using the inverse transform approach by obtaining the Lindley variates numerically; we also generated data from this distribution using the composition approach. Following the generation of the Lindley variates using these two methods, we compare some statistical properties of the estimates of the Lindley model parameters based on the generated data. We conclude that the two methods produce similar results.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.117-133
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• 2008

Although development density control has received murk attention in urban planning, there has been little research on empirical methods that can examine local changes in development density. Recently, attempts have been made to develop cellular automata (CA) models that can be applied to urban landuse change. This paper aims to develop an extended landuse change model based on urban CA considering development density. The proposed model not only includes density control component in a model framework, but also directly estimates local density changes in land use. The developed model was applied to the study area, which was a part of central Seoul. The calibration of the model was carried out over the period $1900s\sim2000s$ using parcel-based land use data and related variables The results of the calibrated model have been tested by comparison with actual landuse data, and have demonstrated that the developed model can produce realistic simulations of urban landuse changes. But model output is dependent on the spacio-temporal resolution of input data. Further research is necessary to improve the calibration procedure and methods for evaluating model validity.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.133-141
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• 2021

The probe vehicle penetration rate is a required parameter in the estimation of entire volume, density, and queue length from probe vehicle data. The previous studies have proposed estimation methods without point detectors, which are based on probability structures for the locations of probe and non-probe vehicles; however, such methods are poorly suited to the case of multi-lane streets. Therefore, this study aimed to estimate the probe vehicle penetration rate at a multi-lane intersection and introduce a probability distribution of the queue length of each lane. Although a gap between estimates and observations was found, the estimates followed the trend of observations; the estimation could be improved by the correction factor hereafter. This study is expected to be used as a basic study for the estimation of entire volume, density, and queue length at multi-lane intersections without point detectors.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.42 no.6
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• pp.642-649
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• 2009

Line transect data from sighting surveys conducted in the East Sea, Korea in 2000, 2002, 2003, 2005 and 2006 were analysed to estimate densities and numbers of minke whale. The half-normal model was fit to the survey in 2000 and the uniform model was the most fitable to the survey in 2002 and 2006, and the surveys in 2003 and 2005 were fit by the hazard-rate model. The estimated density of minke whale in the survey in 2000 was estimated as 0.026 individuals/$km^2$ (CV=0.409; 95% CI 0.011-0.065) and was higher than the survey in 2002 estimated as 0.018 individuals/$km^2$ (CV=0.329; 95% CI: 0.009-0.034). The estimated density of minke whale in the survey in 2003 was estimated as 0.033 individuals/$km^2$ (95% CI: 0.008-0.139) with the highest CV 0.760. The highest density was estimated in the survey in 2005 with 0.053 individuals/$km^2$ (95% CI: 0.020-0.141). The Lowest CV (0.306) was estimated in the survey in 2006 with 0.025 individuals/$km^2$ (95% CI: 0.014-0.046). A total of 500 bootstrap samples were generated within each stratum. Density, CV and 95% CI of each surveys were increased than analytic results except the survey in 2003. There were no increasing or decreasing annual trends in the density of minke whales observed during the study period. A long-term monitor and survey is needed to assess project minke whale abundance in the East Sea.

• Journal of Korea Water Resources Association
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• v.35 no.3
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• pp.307-319
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• 2002

This study used the WGR model to generate the rainfall input and the modified Clark method to estimate the runoff with the aim of investigating how the errors from the areal average rainfall propagates to runoff estimates. This was done for several cases of raingauge density and also by considering several storm directions. Summarizing the study results are as follows. (1) Rainfall and runoff errors decrease exponentially as the raingauge density increases. However, the error stagnates after a threshold density of raingauges. (2) Rainfall errors more affect to runoff estimates when the density of raingauges is relatively low. Generally, the ratio between estimation errors of rainfall and runoff volumes was found much less than one, which indicates that there is a smoothing effect of the basin. However, the ratio between estimation errors of rainfall to peak flow becomes greater than one to indicate the amplification of rainfall effect to peak flow. (3) For the study basin in this studs no significant effect of storm direction could be found. However, the runoff error becomes higher when the storm and drainage directions are identical. Also, the error was found higher for the peak flow than for the overall runoff hydrograph.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.503-516
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• 2019

We have estimated the vertical column density (VCD) of formaldehyde (HCHO) on a global scale using a multiple linear regression method (MRM) with Ozone Monitoring Instrument (OMI) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data. HCHO VCDs were estimated in regions of biogenic, pyrogenic, and anthropogenic emissions using independent variables, including $NO_2$ VCD, land surface temperature (LST), an enhanced vegetation index (EVI), and the mean fire radiative power (MFRP), which are strongly correlated with HCHO. To evaluate the HCHO estimates obtained using the MRM, we compared estimates of HCHO VCD data measured by OMI ($HCHO_{OMI}$) with those estimated by multiple linear regression equations (MRE) ($HCHO_{MRE}$). Good MRM performances were found, having the average statistical values (R = 0.91, slope = 1.03, mean bias = $-0.12{\times}10^{15}molecules\;cm^{-2}$, percent difference = 11.27%) between $HCHO_{MRE}$ and $HCHO_{OMI}$ in our study regions where high HCHO levels are present. Our results demonstrate that the MRM can be a useful tool for estimating atmospheric HCHO levels.