• 제목/요약/키워드: time trend

검색결과 3,737건 처리시간 0.03초

담배가격인상 효과분석 (Analysis of the Effect of Cigarette Price Hike)

  • 김도훈;한광환
    • 한국연초학회지
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    • 제27권2호
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    • pp.235-243
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    • 2005
  • The government continuously increases cigarette price to reduce the smoking rates. Opinions of cigarette makers and Ministry of Health and Welfare on the effect of cigarette price hike are sharply opposed. This dispute is important because there is possibility of additional increase of cigarette price by 500 won. Therefore, as an inquiry into existing studies for the effect of cigarette price hike on tobacco product, namely analysis of the effect of cigarette price hike consumption, we empirically analyzed the effect of cigarette excise tax hike through establishing improved analytic models considering time trend. As a result, it is substantiated that time trend in the effect of cigarette excise tax hike is certainly exist and early impact is heavy. However, the amount of cigarette consumption is recovered to the level of the average in 5 months. Since it is proved that the long term effect of cigarette price hike is immaterial, health authority should reconsider the plan of additional raising cigarette price by 500 won.

시계열 데이터로부터 경향성을 이용한 순차패턴의 탐색 (Rule discovery for sequential patterns of trend from Time-Series)

  • 오용생;남도원;장지숙;이동하;이전영
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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    • pp.325-332
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    • 2000
  • 데이터마이닝 분야에서 시계얼 데이터(time-series data)내에서 숨어 있는 순차패턴의 발견은 상품(Items)이나 어떤 사건(Event)과 같이 데이터의 특징이 명확한 대상에 대한 연구는 많이 되어왔으나 수치 값을 가지는 시계열 데이터에서 이들 내부에 숨어 있는 패턴을 발견하는 것은 최근에 관심을 가지게 되었다. 우리는 시계열 데이터를 시간적 변화에 따라 값의 변화 경향(Trend)이 같은 데이터 그룹을 패턴 요소인 벡터 (Vestor)로 표현하여 이들을 이용해서 흥미로운 패턴들을 발견한다. 이와 같은 벡터적인 표현으로 우리는 벡터들 간의 포함관계를 적용해 모든 가능한 형태의 패턴 발견을 목적으로 한다. 또한 경향성을 가진 패턴 요소를 사건(Event)과 같이 취급함으로써 다양한 종류의 시계열 데이터가 동시에 발생될 때 이들 상호간에 연관된 시간적 패턴을 찾을 수 있다. 따라서 이 연구에서 제안하는 경향성을 기초로 한 순차패턴의 탐식은 기업내부의 판매실적의 변화 패턴이나, 고객의 구매 행동분석에 적용이 가능하리라 여겨진다

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호흡패턴에 따른 성인의 심박수 동태 해석 (The Serial Change Analysis of Heart Rate According to Expiration-to-inspiration Time Ratio in Adults)

  • 박영배;한경숙;남동현
    • 대한예방한의학회지
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    • 제14권2호
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    • pp.105-120
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    • 2010
  • Objectives : This study aims to evaluate the effects of expiration-to-inspiration time ratio (E/I-ratio) on heart rate, which represents cardiac autonomic function, and cold-heat in the healthy people. Methods : 49 healthy young volunteers(male : female = 32 : 17) were recruited in the study. The participants completed the questionnaire for yin-yang pattern identification and then we measured the chest plethysmogram for respiration signal and the electrocardiogram for NN intervals during different E/I-ratio from 1 to 2. We compared heart rate variability including RMS-SD, VLF, LF and HF, and the trend-cycle factors decomposed from NN interval data by time series analysis among the respective E/I-ratio. We also confirmed the difference on the trend-cycle factors according to the score of the questionnaire for cold and heat pattern identification. Results : There were differences on the trend-cycle factors from NN interval data, but no significant difference on heart rate variability, among the respective E/I-ratio. We also found significant relationship between the trend-cycle factors and the heat pattern identification scores. Conclusions : The results indicate that cardiac autonomic function can be modulated by the E/I-ratio and the modulation will be slower and more tendencious than respiratory sinus arrhythmia.

Characteristic Trend Analysis of Cancer Patients Hospitalized in Shanxi Tumor Hospital for the First Time during 2001 and 2010

  • Zhang, Wen-Li;Wang, Yan;Han, Cun-Zhi
    • Asian Pacific Journal of Cancer Prevention
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    • 제16권9호
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    • pp.3673-3676
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    • 2015
  • To observe and analyze the characteristic trend of cancer patients hospitalized for the first time in Shanxi Tumor Hospital from 2001 to 2010, clinical data including case number, age, gender, and frequency of different tumor occurrences were collected and statistically analyzed. Results: (i) From 2001 to 2010, the number of cancer patients hospitalized for the first time increased by 1.3-fold; (ii) The patient overall average age also increased from 51.8 to 54.4, for males from 55.5 to 58.7 and females from 48.4 to 51.1, respectively. (iii) Male patients accounted for 43-48% and females accounted for 52-57% of the total. The percentage of female patients was higher than that of male patients in every year and showed an upward trend over the years, while that of the males showed a downward trend (${\chi}^2=7.031$, p=0.008); (iv) Among the top 6 most common cancers, lung, cervical, esophageal, colorectal and breast cancers tended to increase over the years (p<0.05), but not gastric cancer (p=0.423). Conclusions: (i) The number of cancer patients hospitalized for the first time during the past 10 years increased year by year, and was higher for female than male; (ii) the average age of patients increased year after year and was greater for male than female; (iii) the number of patients with lung cancer, cervical cancer, esophageal cancer, colorectal cancer and breast cancer increased over years.

트렌드와 계절성을 가진 시계열에 대한 순수 모형과 하이브리드 모형의 비교 연구 (Comparison Studies of Hybrid and Non-hybrid Forecasting Models for Seasonal and Trend Time Series Data)

  • 정철우;김명석
    • 지능정보연구
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    • 제19권1호
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    • pp.1-17
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    • 2013
  • 본 연구에서는 시계열 예측을 위해 선형 모형과 비선형 모형의 하이브리드 모형 및 순수 모형의 성과를 비교 평가하였다. 이를 위해 5가지 서로 다른 패턴을 가지는 데이터를 생성하여 시뮬레이션을 진행하였다. 본 연구에서 고려한 선형 모형은 AR(autoregressive model)과 SARIMA(seasonal autoregressive integrated moving average model)이고 비선형 모형은 인공신경망(artificial neural networks model)과 GAM(generalized additive model)이다. 특히, GAM은 여러 장점에도 불구하고 시계열 예측을 위한 비선형 모형으로 기존 연구들에서는 거의 쓰이지 않았던 모형이다. 시뮬레이션 결과, seasonality를 가지는 시계열에 대해서는 AR 및 AR-AR 모형이, trend를 가지는 시계열에 대해서는 SARIMA 및 SARIMA와 다른 모형의 하이브리드 모형이 다른 모형에 비해 높은 성과를 보였다. 한편, 인공신경망과 GAM을 비교하면, 트렌드와 계절성이 더해진 시계열에 대해 SARIMA와 GAM의 하이브리드 모형이 거의 모든 노이즈(noise) 수준에 대해 높은 성과를 보인 반면, 노이즈 수준이 미미한 경우에 한해 SARIMA와 인공신경망의 하이브리드 모형이 높은 성과를 보였다.

구간 고장 데이터가 주어진 수리가능 시스템의 신뢰도 분석절차 개발 및 사례연구 (Development of Reliability Analysis Procedures for Repairable Systems with Interval Failure Time Data and a Related Case Study)

  • 조차현;염봉진
    • 한국군사과학기술학회지
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    • 제14권5호
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    • pp.859-870
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    • 2011
  • The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.

수질자료의 추세분석을 위한 비모수적 통계검정에 관한 연구 (A Study of Non-parametric Statistical Tests to Analyze Trend in Water Quality Data)

  • 이상훈
    • 환경영향평가
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    • 제4권2호
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    • pp.93-103
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    • 1995
  • This study was carried out to suggest the best statistical test to analyze the trend in monthly water quality data. Traditional parametric tests such as t-test and regression analysis are based on the assumption that the underlying population has a normal distribution and regression analysis additionally assumes that residual errors are independent. Analyzing 9-years monthly COD data collected at Paldang in Han River, the underlying population was found to be neither normal nor independent. Therefore parametric tests are invalid for trend detection. Four Kinds of nonparametric statistical tests, such as Run Test, Daniel test, Mann-Kendall test, and Time Series Residual Analysis were applied to analyze the trend in the COD data, Daniel test and Mann-Kendall test indicated upward trend in COD data. The best nonparametric test was suggested to be Daniel test, which is simple in computation and easy to understand the intuitive meaning.

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복합 추세를 가지는 수리가능 시스템의 고장 데이터 모형화에 관한 연구 (Research for Modeling the Failure Data for a Repairable System with Non-monotonic Trend)

  • 문병민;배석주
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제9권2호
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    • pp.121-130
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    • 2009
  • The power law process model the Rate of occurrence of failures(ROCOF) with monotonic trend during the operating time. However, the power law process is inappropriate when a non-monotonic trend in the failure data is observed. In this paper we deals with the reliability modeling of the failure process of large and complex repairable system whose rate of occurrence of failures shows the non-monotonic trend. We suggest a sectional model and a change-point test based on the Schwarz information criterion(SIC) to describe the non-monotonic trend. Maximum likelihood is also suggested to estimate parameters of sectional model. The suggested methods are applied to field data from an repairable system.

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섬유 신소재 개발 Trend에 대한 고찰 (An Analysis of New Textile Material Developmental Trend)

  • 이유경;김순심
    • 한국농촌생활과학회지
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    • 제6권1호
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    • pp.11-24
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    • 1995
  • The new textile materials may be defined as textile materials different from already existing ones in the physical and chemical structure, manufacturing process, or end-use property. The present time what is called the post-industrial society is characterized by rapid change and new technology. Also, textile materials have been changed rapidly and diversely in the post-industrial society than in any other periods. The study aimed to analyze the trend of new tektite materials development in Korea and to forecast the development trend in the future. To investigate the trend of new textile materials, various written materials and informations were collected from the manufacturers, textile related periodicals, and research journals, and they were analyzed. The period of analysis was from January 1992 to May 1995. The results of this research are as followings : (1) Mixed textile materiasl such as bicomponent fiber, blended yam and blended fabric were increased. (2) High technology has an important effect upon new textile material development. (3) functional textile materials were increased (4) The high value-added products were increased. (5) The naturalized textile materials were increased.

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What is the Most Suitable Time Period to Assess the Time Trends in Cancer Incidence Rates to Make Valid Predictions - an Empirical Approach

  • Ramnath, Takiar;Shah, Varsha Premchandbhai;Krishnan, Sathish Kumar
    • Asian Pacific Journal of Cancer Prevention
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    • 제16권8호
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    • pp.3097-3100
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    • 2015
  • Projections of cancer cases are particularly useful in developing countries to plan and prioritize both diagnostic and treatment facilities. In the prediction of cancer cases for the future period say after 5 years or after 10 years, it is imperative to use the knowledge of past time trends in incidence rates as well as in population at risk. In most of the recently published studies the duration for which the time trend was assessed was more than 10 years while in few studies the duration was between 5-7 years. This raises the question as to what is the optimum time period which should be used for assessment of time trends and projections. Thus, the present paper explores the suitability of different time periods to predict the future rates so that the valid projections of cancer burden can be done for India. The cancer incidence data of selected cancer sites of Bangalore, Bhopal, Chennai, Delhi and Mumbai PBCR for the period of 1991-2009 was utilized. The three time periods were selected namely 1991-2005; 1996-2005, 1999-2005 to assess the time trends and projections. For the five selected sites, each for males and females and for each registry, the time trend was assessed and the linear regression equation was obtained to give prediction for the years 2006, 2007, 2008 and 2009. These predictions were compared with actual incidence data. The time period giving the least error in prediction was adjudged as the best. The result of the current analysis suggested that for projections of cancer cases, the 10 years duration data are most appropriate as compared to 7 year or 15 year incidence data.