• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.9-20
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• 1990

The purpose of this paper is to propose the modified semiparametric estimators for survival function in the Cox's regression model with randomly censored data based on Tsiatis and Breslow estimators, and present their asymptotic variances estimates. The proposed estimators are compared to Tsiatis, Breslow, and Kaplan-Meier estimators through a small-sample Monte Carlo study. The simulation results show that the proposed estimators are preferred for small sample sizes.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.155-170
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• 1997

We propose an integer-valued MA(q) process with Poisson disturbance. Its various properties are discussed such as the joint distribution, time reversibility and regression. We derive the asymptotic distribution of autocovariance function and estimators of the parameters in the suggested model. We also consider the relationship between INMA(q) and M/D/.infty. processes.

• Journal of Families and Better Life
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• v.17 no.3
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• pp.131-144
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• 1999

The purpose of this study was to examine the influences of the consumer's knowledge the consumer's attitude the family characteristics and the variables on consumer socialization to the consumer's functions of homemakers. The samples were selected from 428 homemakers living in Kwangju, Frequncies Perentiles Means Standard Deviations Multiple regression Path analysis were used as statistical analysis The results were sumarized as follows: Resulting from multiple regression analysis the consumer's function had the positive linear relationships with variables such as family life cycles interaction with family consume knowledge and consumer attitude. The most influential variable was consumer attitude.

• Journal of Korean Society of Forest Science
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• v.83 no.4
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• pp.521-530
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• 1994

Voume functions, which are usually expressed by the function of dbh and height, are estimated commonly through the regression analysis with the highest statistical accuracy considered. In Korea, general volume functions for each tree species were prepared by means of the regression analysis with the exponential function ($V=aD^bH^c$) having the dbh(D) and height(H) as independent variables. In this study, regional stem curve functions for the Pinus densiflora in Kangwon-province were derived and a regional volume function model, in which the stem volume can be directly estimated through the rotational integral of the regional stem curve functions, was prepared. The regional volume estimated by the prepared model was more accurate than the volume by the general volume table for the Pinus densiflora in Kangwon-province. Additionary, the form of stem curves derived by the regional stem curve functions showed difference from each other. The stem in Youngwol and Wonju taper down more fast in upper part than that in other regions. These various stem forms also led to the regional difference in volume estimates.

• 한국노년학
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• v.39 no.2
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• pp.389-404
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• 2019

The present study aims to examine the relationship between self-reported sensory impairment and cognitive function among older adults in Korea. Drawn from the 2017 Survey of Living Conditions and Welfare Needs Korean Older Persons, a total of 10,082 adults aged 65 and over were included in analyses. Results from hierarchial multiple regression analysis show that those who reported greater subjective discomfort about vision, hearing, and oral function were more likely to have poor cognitive function. Results from hierarchial logistic regression analysis show. Results from logistic regression analysis show that having hearing and oral discomfort increased the a risk for dementia. Findings suggest that it is necessary to manage sensory function of the elderly at the government level and to develop self-evaluation tools to monitor changes in sensory function for older adults. Future research should target finding effective ways to improve health of older adults.

• Journal of Korean Society of Transportation
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• v.8 no.2
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• pp.77-97
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• 1990

Compared to modal split, the methods of forecasting traffic volumes diverted in various types of I.C.s have not been sufficiently studied. The purpose of this study is to derive a new diversion function that can represent the directional traffic volume in accordance with various geometrics of I.C.s. In general, knowing various traffic impedances and the amount of traffic production and attraction, one can estimate proper traffic volumes associated with directions by using a well-defined diversion function. This function is usually made by a series of process such as surveying directional traffic volumes on several I.C.s, analyzing with a regression method and verifying those results by statistical approaches. The function has been developed by rigorous statistical testings, mainly a regression analysis. This paper presents an effective method in planning and designing new roads, I.C.s and route choice of subway. Finally, some comparisons and improvements and suggested when one uses different types of relevant models and functions.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.04a
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• pp.217-220
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• 2003

In the case of the remediation studies, push pull test is a more time and cost effective mettled than multi-well tracer test. It also gives Just as much or more information than the traditionally used methods. But the data analysis for the hydraulic parameters, there have been some defections such as underestimation of dispersivity, requirement for effective porosity, and calculation of recovery of center of mass to estimate linear velocity. In this research, Weibull distribution function is proposed to estimate the center of mass of breakthrough curve for Push pull test. The hydraulic parameter estimation using Weibull function showed more exact values of center of mass than those of exponential regression for field test data.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.127-134
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• 1997

A method is proposed for the choice of the number of principal components in principal component regression based on the predicted error sum of squares. To do this, we approximately evaluate that statistic using a linear approximation based on the perturbation expansion. In this paper, we apply the proposed method to various data sets and discuss some properties in choosing the number of principal components in principal component regression.

• Journal of the Korean Data and Information Science Society
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• v.14 no.1
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• pp.119-129
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• 2003

We propose a new logistic regression model of normality curves for normal(diseased) and abnormal(nondiseased) classifications by neural networks in data mining. The fitted logistic regression lines are estimated, interpreted and plotted by the neural network technique. A few goodness-of-fit test statistics for normality are discussed and the performances by the fitted logistic regression lines are conducted.