• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.983-988
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• 2003

When the available sample is multiply Type-II censored, the maximum likelihood estimators of the location and the scale parameters of two-parameter exponential distribution do not admit explicitly. In this case, we propose some approximate maximum likelihood estimators by approximating the likelihood equations appropriately. We present an example to illustrate these estimation methods.

• 한국해양학회지
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• v.12 no.1
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• pp.13-32
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• 1977

In order to determine the distributional ecology, and to investigate factors influencing these features, the diatom communities in plankton at depths of one, twenty-five, fifty, and seventy five meters in the area were studied and measured over a fifteen month of period. Measurements of environmental factors including temperature and salinity and algal nutrients such as phosphate, silicate, nitrate, and ammonia were also made at the same depths and locations. The results indicate that the size of diatom communities and the species population changes were heavily dependent upon to season and location parameters as well as nutrient concentrations and hydrographic factors. Major factors influencing population distributions varied with principal species responsible for dominant species and species sucession. Two distinct distributional patterns in total diatom crop were observed in the study area. Maximum standing crop observed during spring and/or summer were related to the concentration of nutrients available at the onset of the spring bloom on a large scale. On a small scale, however, the distributions of total diatom standing crops were significantly correlated with both season/location factors and with hydrographic parameters as well. Vertical stratification of diatoms was observed only in the presence of the thermocline in the water column. Within the study area there was some seasonal consistancy in the composition of the species groups. However, some species association in these environments may vary with the change of season.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.457-470
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• 2003

The comparison of two or more Lorenz curves of Pareto distributions of first kind under arbitrary order restriction is studied. The problem is turned out to be a statistical inference problem concerning scale parameters under order restriction. We assume that the location parameters of Palate distributions are completely unknown. In this paper the maximum likelihood estimation and likelihood ratio tests for and against order restriction are proposed.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.47-55
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• 2020

In this paper, we propose one stage multi-scale face detector based Fully Convolution Network using anchor free method. Recently almost all state-of-the-art face detectors which predict location of faces using anchor-based methods rely on pre-defined anchor boxes. However this face detectors need to hyper-parameters and additional computation in training. The key idea of the proposed method is to eliminate hyper-parameters and additional computation using anchor free method. To do this, we apply two ideas. First, by eliminating the pre-defined set of anchor boxes, we avoid the additional computation and hyper-parameters related to anchor boxes. Second, our detector predicts location of faces using multi-feature maps to reduce foreground/background imbalance issue. Through Quantitative evaluation, the performance of the proposed method is evaluated and analyzed. Experimental results on the FDDB dataset demonstrate the effective of our proposed method.

• Water for future
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• v.28 no.4
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• pp.185-194
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• 1995

The objective of this study is to explore scale problem and to analyze the relations between scale and geomorphologic parameters of the rainfall-runoff model. Generally, measurement and calculation of geomorphologic parameters rely on and are sensitive to the resolution of source information available. Therefore, rainfall-runoff models using geomorphologic parameters should take account of the effects of the map scale used in their development. The derived rainfall-runoff model considering scale problem in this research is the GIUH type model, that is a basin IUH consisting of the channel network response and hillslope response. The cannel network response is computed by means of the diffusion analogy transformed from linearized St. Venant equation and hillslope response is calculated by 2-parameter gamma distribution function. Representing geomorphologic structure of the channel network and initial distribution of its response is width function. This width function is derived by fractal theory and Melton's law to consider scale problems and is weighted by the source location function (SLF) proposed in this research to increase the applicability.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1327-1335
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• 2010

In this paper, we want to develop objective priors for the common location parameter in two half-t distributions with unequal scale parameters. The half-t distribution is a non-regular class of distribution. One can not develop the reference prior by using the algorithm of Berger of Bernardo (1989). Specially, we derive the reference priors and prove the propriety of joint posterior distribution under the developed priors. Through the simulation study, we show that the proposed reference prior matches the target coverage probabilities in a frequentist sense.

• Journal of Wetlands Research
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• v.14 no.3
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• pp.341-352
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• 2012

The purpose of this study is to statistically project future probable rainfall and to quantitatively assess a future flood vulnerability using flood vulnerability model. To project probable rainfall under non-stationarity conditions, the parameters of General Extreme Value (GEV) distribution were estimated using the 1 yr data added to the initial 30 yr base series. We can also fit a linear regression model between time and location parameters after comparing the linear relationships between time and location, scale, and shape parameters, the probable rainfall in 2030 yr was calculated using the location parameters obtained from linear regression equation. The flood vulnerability in 2030 yr was assessed inputted the probable rainfall into flood vulnerability assessment model suggested by Jang and Kim (2009). As the result of analysis, when a 100 yr rainfall frequency occurs in 2030 yr, it was projected that vulnerability will be increased by spatial average 5 % relative to present.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2172-2178
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• 2007

In indoor environment, the combination of the two variations, large scale(path loss) and small scale(fading), leads to non-linear variation of RSSI(received signal strength indicator) values as distance varied. This has been one of the difficulties for indoor location estimation. This paper presents new findings on indoor RSSI characterization for more accurate model building. Experiments have been done statistically to find overall trend of RSSI values at different places and times within the same room. From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. These two factors are directly indicated by the two main parameters of path loss model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. The temporal parameter also has a large scale variation effect that is slowly time varying due to environmental changes. Using this relationship, the characterization for location estimation can be more efficient and accurate.

• Communications for Statistical Applications and Methods
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• v.23 no.4
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• pp.321-334
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• 2016

In this paper, we propose power t distribution based on t distribution. We also study the properties of and inferences for power t model in order to solve the problem of real data showing both skewness and heavy tails. The comparison of skew t and power t distributions is based on density plots, skewness and kurtosis. Note that, at the given degree of freedom, the kurtosis's range of the power t model surpasses that of the skew t model at all times. We draw inferences for two parameters of the power t distribution and four parameters of the location-scale extension of power t distribution via maximum likelihood. The Fisher information matrix derived is nonsingular on the whole parametric space; in addition we obtain the profile log-likelihood functions on two parameters. The response plots for different sample sizes provide strong evidence for the estimators' existence and unicity. An application of the power t distribution suggests that the model can be very useful for real data.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.103-110
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• 2011

Exponential distribution is widely adopted as a lifetime model. Many authors have considered the interval estimation of the parameters of two-parameter exponential distribution based on complete and censored samples. In this paper, we consider the interval estimation of the location and scale parameters and the joint confidence region of the parameters of two-parameter exponential distribution based on upper records. A simulation study is done for the performance of all proposed confidence intervals and regions. We also propose the predictive intervals of the future records. Finally, a numerical example is given to illustrate the proposed methods.