• 제목/요약/키워드: Growth Curve

검색결과 1,037건 처리시간 0.033초

Error Structure of Technological Growth Models A Study of Selection Techniques for Technological Forecasting Models

  • Oh, Hyun-Seung;Yim, Dong-Soon;Moon, Gee-Ju
    • 품질경영학회지
    • /
    • 제23권1호
    • /
    • pp.95-105
    • /
    • 1995
  • The error structure of nonlinearized technological growth models, such as, the Pearl curve, the Gompertz curve and the Wei bull growth curve, has zero mean and a constant variance over time. Transformed models, however, like the linearized Fisher-Pry model. the linearized Gompertz growth curve, and the linearized Weibull growth curve have increasing variance from t = 0 to the inflection point.

  • PDF

마케팅자료에서 특성점들을 이용한 군집방법 (Clustering Method Using Characteristic Points with Marketing Data)

  • 문숙경;김우성
    • 품질경영학회지
    • /
    • 제32권4호
    • /
    • pp.265-273
    • /
    • 2004
  • We got the growth distance curve by spline smoothing method with observed marketing data and the growth velocity curve by the derivation of the growth distance curve. Using this growth velocity curve, we defined the several characteristic points which describe the variation of marketing data. In this paper, to specify several patterns of marketing data, we suggested characteristic function by using these characteristic points. In addition, we applied characteristic function to the seventeen brands of electric home products data.

비선형 성장곡선 모형의 분석 절차에 대한 연구 (A Study on the Analysis Procedures of Nonlinear Growth Curve Models)

  • 황정연
    • 품질경영학회지
    • /
    • 제25권1호
    • /
    • pp.44-55
    • /
    • 1997
  • In order to determine procedures for a, pp.opriate model selection of technological growth curves, numerous time series that were representative of growth behavior were collected according to data characteristics. Three different growth curve models were fitted onto data sets in an attempt to determine which growth curve models achieved the best forecasts for types of growth data. The analysis of the results gives rise to an a, pp.oach for selecting a, pp.opriate growth curve models for a given set of data, prior to fitting the models, based on the characteristics of the goodness of fit test.

  • PDF

Estimation of genetic relationships between growth curve parameters in Guilan sheep

  • Hossein-Zadeh, Navid Ghavi
    • Journal of Animal Science and Technology
    • /
    • 제57권5호
    • /
    • pp.19.1-19.6
    • /
    • 2015
  • The objective of this study was to estimate variance components and genetic parameters for growth curve parameters in Guilan sheep. Studied traits were parameters of Brody growth model which included A (asymptotic mature weight), B (initial animal weight) and K (maturation rate). The data set and pedigree information used in this study were obtained from the Agricultural Organization of Guilan province (Rasht, Iran) and comprised 8647 growth curve records of lambs from birth to 240 days of age during 1994 to 2014. Marginal posterior distributions of parameters and variance components were estimated using TM program. The Gibbs sampler was run 300000 rounds and the first 60000 rounds were discarded as a burn-in period. Posterior mean estimates of direct heritabilities for A, B and K were 0.39, 0.23 and 0.039, respectively. Estimates of direct genetic correlation between growth curve parameters were 0.57, 0.03 and -0.01 between A-B, A-K and B-K, respectively. Estimates of direct genetic trends for A, B and K were positive and their corresponding values were $0.014{\pm}0.003$ (P < 0.001), $0.0012{\pm}0.0009$ (P > 0.05) and $0.000002{\pm}0.0001$ (P > 0.05), respectively. Residual correlations between growth curve parameters varied form -0.52 (between A-K) to 0.48 (between A-B). Also, phenotypic correlations between growth curve parameters varied form -0.49 (between A-K) to 0.47 (between A-B). The results of this study indicated that improvement of growth curve parameters of Guilan sheep seems feasible in selection programs. It is worthwhile to develop a selection strategy to obtain an appropriate shape of growth curve through changing genetically the parameters of growth model.

J-적분을 이용한 균열 찢어짐 불안정성에 관한 연구 (Traring instability of crack based on J-integral)

  • 이홍서;김희송
    • 한국정밀공학회지
    • /
    • 제6권3호
    • /
    • pp.78-89
    • /
    • 1989
  • Applicability of tearing modulus based on J-integral proposed by Paris et al is investigated using compact tension specimens of strutural alloy steel (SCM4). Both general fracture test and instability fracture test are performed. The applied tearing modulus, ( $T_{j}$)app estimated from the real load vs. crack growth curve measured from experiments are compared with that estimated from the limit load vs. crack growth curve. The results are : (1) the $T_{j}$parameter could be applied to predict crack growth instability : (2) The use of ( $T_{j}$)app estimated from the load vs. crack growth curve, proposed in this study could be well predicted crack growth instability instead of that estimated form the limit load vs. crack growth curve.e.

  • PDF

On Multiple Comparisons of Randomized Growth Curve Model

  • Shim, Kyu-Bark;Cho, Tae-Kyoung
    • 한국데이터정보과학회:학술대회논문집
    • /
    • 한국데이터정보과학회 2001년도 추계학술대회
    • /
    • pp.67-75
    • /
    • 2001
  • A completely randomized growth curve model was defined by Zerbe(1979). We propose the fully significant difference procedure for multiple comparisons of completely randomized growth curve model. The standard F test is useful tool to multiple comparisons of the completely randomized growth curve model. The proposed method is applied to experimental data.

  • PDF

Outlier Detection in Growth Curve Model

  • Shim, Kyu-Bark
    • Journal of the Korean Data and Information Science Society
    • /
    • 제14권2호
    • /
    • pp.313-323
    • /
    • 2003
  • For the growth curve model with arbitrary covariance structure, known as unstructured covariance matrix, the problems of detecting outliers are discussed in this paper. In order to detect outliers in the growth curve model, the test statistics using U-distribution is established. After detecting outliers in growth curve model, we test homo and/or hetero-geneous covariance matrices using PSR Quasi-Bayes Criterion. For illustration, one numerical example is discussed, which compares between before and after outlier deleting.

  • PDF

SiC 휘스커 보강 알루미나 복합재료에서 Slow Crack Growth 현상의 직접관찰 연구 (In Situ Observation of Slow Crack Growth in a Whisker-Reinforced Alumina Matrix Composite)

  • 손기선;김우상;이성학
    • 한국세라믹학회지
    • /
    • 제33권2호
    • /
    • pp.203-213
    • /
    • 1996
  • In this study the subcritical crack growth behavior in an Al2O3-SiCw composite has been investigated using in situ fracture technique of applied moment double cantilever beam (AMDCB) specimens indside an SEM. This technique allows the detailed observation of whisker and grain bridging in the crack wake region. The experimental results indicated that the KI-a curve was deviated from the conventional powder law form and that the existed a region where the rate of microcrack growth was decreased with increasing the externally applied stress intensity factor. This behavior could be explained by arising crack growth resistance i.e. R-curve behavior which was associated with crack shielding due to whisker and grain bridging. The R-curve was also analyzed from the KI-a curve data in order to quantify the bridging effect in the Al2O3-SiCw composite.

  • PDF

M-추정을 사용한 국방과학기술 수준조사 기술성장모형의 이상치 제거 (Elimination of Outlier from Technology Growth Curve using M-estimator for Defense Science and Technology Survey)

  • 김장헌
    • 한국군사과학기술학회지
    • /
    • 제23권1호
    • /
    • pp.76-86
    • /
    • 2020
  • Technology growth curve methodology is commonly used in technology forecasting. A technology growth curve represents the paths of product performance in relation to time or investment in R&D. It is a useful tool to compare the technological performances between Korea and advanced nations and to describe the inflection points, the limit of improvement of a technology and their technology innovation strategies, etc. However, the curve fitting to a set of survey data often leads to model mis-specification, biased parameter estimation and incorrect result since data through survey with experts frequently contain outlier in process of curve fitting due to the subjective response characteristics. This paper propose a method to eliminate of outlier from a technology growth curve using M-estimator. The experimental results prove the overall improvement in technology growth curves by several pilot tests using real-data in Defense Science and Technology Survey reports.

성장곡선을 이용한 소프트웨어 비용 추정 모델 (A Software Cost Estimation Using Growth Curve Model)

  • 박석규;이상운;박재흥
    • 정보처리학회논문지D
    • /
    • 제11D권3호
    • /
    • pp.597-604
    • /
    • 2004
  • 정확한 소프트웨어 비용 추정은 개발자와 고객 모두에게 중요하다. 대부분의 비움 추정 모델들은 규모 추정으로부터 틴은 라인 수와 기능점수와 같을 규모 측도에 기반을 두고 있다. 규모 추정의 정확도는 비용 추정 정확도에 직접적으로 영향을 미친다. 이에 따라 대부분의 회귀기반 비용추정 모델들은 규모에 기반한 멱함수 형태를 적용하고 있다. 생물의 성장, 기술의 발전과 인간의 학습 능력 등 많은 성장 현상들은 S자 곡선을 따른다. 본 논문은 성장곡선을 이용하여 개발노력을 추정하는 모델을 제시하였다. 제시된 모델은 소프트웨어 규모가 증가함에 따라 소요되는 개발 비용이 성장곡선을 따른다고 가정한다. 일반적인 소프트웨어 규모 추정 기법인 기능점수, 완전기능점수와 유스케이스 점수에 기반하여 성장곡선 모델의 적합성을 검증하였다. 제안된 성장곡선 모델들은 멱함수 모델과 비교 시 상호 견줄만한 성능을 보여 소프트웨어 비용 추정분야에 석용 가능함을 보였다.