• Journal of Technology Innovation
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• v.23 no.1
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• pp.87-105
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• 2015

This research confirms a non-linear relationship between R&D investment and performance of small and medium-sized enterprises and measures the adequate level as threshold value. Although previous studies did not consider the time lag and estimated indirectly the level using the R&D investment squared term, this study assumes 2 years time lag and uses the threshold estimation model to measure directly. We find that there is the S-curve relationship between the profit rate as R&D output and R&D intensity and the ratio of researchers to employees as R&D input. Also, we estimate the adequate levels of R&D investment, 6.4% for R&D intensity and 13% for the ratio of researchers to employees. This relationship and measurement of the level can offer basic facts and implications about R&D policy and strategy.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.101-105
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• 2005

호남지역에 대한 대설특보 예보를 위한 통계모형 개발을 수행하였다. 일 신적설량에 따라 세법주(0: 비발생, 1: 대설주의보, 2: 대설경보)로 구분되는 순서형 자료 형태를 지니고 있다. 두가지 통계 모형(다등급 로지스틱 회귀모형, 신경회로망 모형)을 고려하였으며, 수치모델 출력자료를 이용한 역학-통계모형 기법의 하나인 MOS(model output statistics)를 적용하여 축적된 수치모델 예보자료와 관측치의 관계를 통계모형식으로 추정하여 예측모형을 개발하였다. 군집분석을 사용하여 훈련자료와 검증자료를 구분하였으며, 예보치 생성을 위하여 문턱치를 고려하였다.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.289-299
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• 2015

The objective of the present study is to develop statistical quantitative forecast model for PM10 concentration over Seoul. We used three types of data (weather observation data in Korea, the China's weather observation data collected by GTS, and air quality numerical model forecasts). To apply the daily forecast system, hourly data are converted to daily data and then lagging was performed. The potential predictors were selected based on correlation analysis and multicollinearity check. Model validation has been performed for checking model stability. We applied two models (multiple regression model and threshold regression model) separately. The two models were compared based on the scatter plot of forecasts and observations, time series plots, RMSE, skill scores. As a result, a threshold regression model performs better than multiple regression model in high PM10 concentration cases.