• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.311-318
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• 1993

In this paper, we consider the test based on using Forced question model instead of Warner model and compare the power of two randomized respose models. The estimator for the prportion of the individuals belonging to the sensitive group is obtained by using Forced question model and the conditions that the estimator by Forced question model will be more efficient than the estimators by Warner model are found when the respondents are truthrul in their answers.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1023-1028
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• 2004

A micro-pressure wave is generated by the high-speed train which enters a tunnel, and it causes explosive noise and vibration at the exit. It is known that train speed, train-tunnel area ratio, nose slenderness and nose shape mainly influence on generating micro-pressure wave. So it is required to minimize it by searching optimal values of such train shape factors and tunnel condition. In this study, response surface model, one of approximation models, is used to perform optimization effectively and analyze sensitivity of design variables. Owen's randomized orthogonal array and D-optimal Design are used to construct response surface model. In order to increase accuracy of model, stepwise regression is selected. Finally SQP(Sequential Quadratic Programming) optimization algorithm is used to minimize the maximum micro-pressure wave by using built approximation model.

• The Korean Journal of Applied Statistics
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• v.4 no.2
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• pp.179-193
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• 1991

In this paper, we introduce various methods of PR techniques initiated by S. Warner in 1960's and examine the maximum likelihood estimator for them. One of the main subjects of this paper is to represent Warner model, Unrelated Question Model, and Multi-Proportion Model in linear model. The other subject is to study the inference of PR model by using the Bayesian Approach.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.585-591
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• 1999

Warner(1965)의 확률화 응답 모형을 두 번 연속사용하여 응답자들이 일관성 있는 응답을 했다는 가설을 검정하는 검정통계량을 제안했다. 이것은 양측과 단측 대립가설 모두 검정하는데 이용할 수 있으며, 제안된 검정통계량의 조건분포는 정규분포에 근사한다. 이 검정통계량의 조건부 검정력 함수와 비조건부 검정력 함수를 구하였다.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.341-354
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• 2002

This paper is planned to use randomized response technique which is an indirect response technique on internet as a way of obtaining much more precise information, not revealing secrets of responsors, considering that respondents are generally reluctant to answer in a survey to get sensitive information targeting employees, customers, etc.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.591-603
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• 2003

This paper is planned to use randomized response technique which is an indirect response technique on internet as a way of obtaining much more precise information, not revealing secrets of responsors, considering that respondents are generally reluctant to answer in a survey to get sensitive information targeting employees, customers, etc.

• 한국데이터정보과학회:학술대회논문집
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• 2002.06a
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• pp.107-118
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• 2002

This paper is planned to use randomized response technique which is an indirect response technique on internet as a way of obtaining much more precise information, not revealing secrets of responsors, considering that respondents are generally reluctant to answer in a survey to get sensitive information targeting employees, customers, etc.

• The Korean Journal of Applied Statistics
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• v.12 no.1
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• pp.143-152
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• 1999

본 논문에서는 응답자가 민감한 속성을 가지고 있지 않으면 직접 "예"라고 응답하고, 민감한 속성을 가지고 있으면 Greenberg et al.(1969)의 무관질문모형의 확률장치를 이용하여 선택된 질문에 응답을 하는 새로운 무관확률화응답모형을 제안하였다. 그리고, 제안한 모형이 Mangat(1994)의 관련질문모형보다 효율적인 되는 조건을 제시하였고, 수치적으로 효율성을 비교하였다. 또한, Leysieffer와 Warner(1976)의 위험함수와 Flinger et al.(1977)의 사생활 보호 측도를 이용하여 제안한 모형이 Mangat의 관련질문모형에 비하여 개인의 사생활을 보호해 주는 측면에서 더 효율적임을 보였다.효율적임을 보였다.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.141-150
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• 1998

In this paper, we developed one-stage cluster randomized response model for obtaining quantitative data by using the Greenberg et al. model(1971) when the population was made up of sensitive quantitative clusters. We obtained the minimum variance by calculating the cluster's size and the optimum number of sample clusters under the some given constant cost. We compared the efficiency of our model with the Greenberg et al. model by simple random sampling.

• Computers and Concrete
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• v.32 no.6
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• pp.607-613
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• 2023

The objective of this work is to determine the compressive strength of geopolymer concrete utilizing four distinct machine learning approaches. These techniques are known as gradient boosting machine (GBM), generalized linear model (GLM), extremely randomized trees (XRT), and deep learning (DL). Experimentation is performed to collect the data that is then utilized for training the models. Compressive strength is the response variable, whereas curing days, curing temperature, silica fume, and nanosilica concentration are the different input parameters that are taken into consideration. Several kinds of errors, including root mean square error (RMSE), coefficient of correlation (CC), variance account for (VAF), RMSE to observation's standard deviation ratio (RSR), and Nash-Sutcliffe effectiveness (NSE), were computed to determine the effectiveness of each algorithm. It was observed that, among all the models that were investigated, the GBM is the surrogate model that can predict the compressive strength of the geopolymer concrete with the highest degree of precision.