• Title/Summary/Keyword: Logarithmic Regression

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A Software Reliability Growth Model Based on Gompertz Growth Curve (Gompertz 성장곡선 기반 소프트웨어 신뢰성 성장 모델)

  • Park Seok-Gyu;Lee Sang-Un
    • The KIPS Transactions:PartD
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    • v.11D no.7 s.96
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    • pp.1451-1458
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    • 2004
  • Current software reliability growth models based on Gompertz growth curve are all logarithmic type. Software reliability growth models based on logarithmic type Gompertz growth curve has difficulties in parameter estimation. Therefore this paper proposes a software reliability growth model based on the logistic type Gompertz growth curie. Its usefulness is empirically verified by analyzing the failure data sets obtained from 13 different software projects. The parameters of model are estimated by linear regression through variable transformation or Virene's method. The proposed model is compared with respect to the average relative prediction error criterion. Experimental results show that the pro-posed model performs better the models based on the logarithmic type Gompertz growth curve.

Prediction of Prestress Foce Losses by Nonlinear Regression (비선형 회귀분석에 의한 프리스트레스 하중의 사간에 따른 소실 예측)

  • 오병환;양인환;홍경옥;채성태
    • Proceedings of the Korea Concrete Institute Conference
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    • 1998.04a
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    • pp.347-352
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    • 1998
  • The purpose of this paper is to present and establish a procedure to predict the prestress forces during the service life of the structure. The statistical approach of this procedure is using the in-situ measurement data of the post-tensioning system to develop a nonlinear regression analysis. The method of least squares is used to fit a certain function a set of data. Use of a nonlinear model is achieved by its logarithmic transformation and sunsequent use of linear-regression theory. The regression analysis result can be used to check the prestress force during the service life so that the remaining prestress force is equal to or exceeds the design requirement. Results from the measurement data of PSC box girder bridge structure were used to demonstrate the procedures.

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Analysis of Loss Factor for Statistical Modeling for Indoor Environment (실내 환경에서 통계적 모델링을 위한 손실인자 분석)

  • 이권익;홍성욱;강부식;김흥수
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.865-868
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    • 1999
  • In this paper, indoor propagation characteristics are analyzed for various environments such as corridors, walls and corners. In order to present the statistical model for indoor environments the loss factors of each case are obtained by linear regression analysis method with the function of logarithmic distance between transmitter and receiver.

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Verification of Nonpoint Sources Runoff Estimation Model Equations for the Orchard Area (과수재배지 비점오염부하량 추정회귀식 비교 검증)

  • Kwon, Heon-Gak;Lee, Jae-Woon;Yi, Youn-Jeong;Cheon, Se-Uk
    • Journal of Korean Society on Water Environment
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    • v.30 no.1
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    • pp.8-15
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    • 2014
  • In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.

A Study on Modeling and Forecasting of Mobile Phone Sales Trends (이동통신 단말기 판매 추이에 대한 모형 및 수요예측에 관한 연구)

  • Kim, Min-Jeong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.6
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    • pp.157-165
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    • 2016
  • Among high-tech products, the mobile phone has experienced a rapid rate of innovation and a shortening of its product life cycle. The shortened product life cycle poses major challenges to those involved in the creation of forecasting methods fundamental to strategic management and planning systems. This study examined whether the best model applies to the entire diffusion life span of a mobile phone. Mobile phone sales data from a specific mobile service provider in Korea from March of 2013 to August of 2014 were analyzed to compare the performance of two S-shaped diffusion models and two non-linear regression models, the Gompertz, logistic, Michaelis-Menten, and logarithmic models. The experimental results indicated that the logistic model outperforms the other three models over the fitted region of the diffusion. For forecasting, the logistic model outperformed the Gompertz model for the period prior to diffusion saturation, whereas the Gompertz model was superior after saturation approaches. This analysis may help those estimate the potential mobile phone market size and perform inventory and order management of mobile phones.

Estimation of Tunnel Convergence Using Statistical Analysis (통계처리를 활용한 터널 내공변위의 분석에 관한 연구)

  • 김종우
    • Tunnel and Underground Space
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    • v.13 no.2
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    • pp.108-116
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    • 2003
  • Measured convergence data of a tunnel were investigated by means of statistical and regression analysis, where the rock mass were mainly composed of andesite and granite. The rock mass around tunnel were classified by RMR method into five different ratings, and then convergence data which belong to individual ratings were statistically processed to find out the appropriate regression equations. Exponential equations were better coincided with measured data than logarithmic equations. As the number of rock mass rating was increased, the magnitude and standard deviation of convergence were increased. Final convergence data were also investigated to study the relevance with both maximum displacement rate and early measured convergence. Some brief results of their relevance are presented. For instance, the regression coefficient between final convergence and maximum displacement rate was turned out to be 0.87 for this studied tunnel.

Corporate Governance and Performance of Insurance Companies in the Saudi Market

  • OSMAN, Mohamed Abdel Mawla;SAMONTARAY, Durga Prasad
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.4
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    • pp.213-228
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    • 2022
  • This paper investigates the association between key corporate governance characteristics and the performance of general insurance businesses listed on the Saudi stock exchange (TADAWUL). The methodology for the study is based on a pooled data collection for 11 Saudi general insurance companies from 2011 to 20. The linear regression model and the logarithm regression model are suggested to assess the relationship between performance and corporate governance characteristics. The dependent variable is firm performance measured using ROA, ROE, and Tobin's Q. The independent variables are corporate governance variables consisting of a complete set of board and audit committee characteristics. Insurer-specific control variables are introduced. The empirical results reveal that the characteristics of corporate governance influence the performance of insurance companies. In particular, the board size, board's tenure, the proportion of independent directors in the board, audit committee size, audit committee meeting frequency, and proportion of health insurance premiums have a positive impact. However, audit committee independence, size of the company, and proportion of reinsurance premiums have a negative impact on the performance of the Saudi general insurance companies. Finally, the empirical results indicated also that there is an unclear relationship between the performance and board meeting frequency, compensations of the Board, and the average age of the Board.

Bayesian curve-fitting with radial basis functions under functional measurement error model

  • Hwang, Jinseub;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.3
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    • pp.749-754
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    • 2015
  • This article presents Bayesian approach to regression splines with knots on a grid of equally spaced sample quantiles of the independent variables under functional measurement error model.We consider small area model by using penalized splines of non-linear pattern. Specifically, in a basis functions of the regression spline, we use radial basis functions. To fit the model and estimate parameters we suggest a hierarchical Bayesian framework using Markov Chain Monte Carlo methodology. Furthermore, we illustrate the method in an application data. We check the convergence by a potential scale reduction factor and we use the posterior predictive p-value and the mean logarithmic conditional predictive ordinate to compar models.

A Numerical Modelling for the Prediction of Phase Transition Time(Ice-Water) in Frozen Gelatin Matrix by Ohmic Thawing Process

  • Kim, Jee-Yeon;Park, Sung-Hee;Min, Sang-Gi
    • Proceedings of the Korean Society for Food Science of Animal Resources Conference
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    • 2004.10a
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    • pp.407-411
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    • 2004
  • Ohmic heating occurs when an electric current is passes through food, resulting in a temperature rise in the product due to the conversion of the electric energy into heat. The time spent in the thawing is critical for product sterility and quality. The objective of this study is to conduct numerical modelling between the effect of ohmic thawing intensity on PTT(phase transition time) at constant concentration and the effect of matrix concentrations on PTT at constant voltage condition. the stronger ohmic thawing intensity resulted in decreasing the PTT. High ohmic intensity causes short PTT. And the higher gelatin concentration, the faster increment of PTT. A numerical modeling was executed to predict the PTT influenced by the power intensity using exponential regression and the PTT influenced by gelatin concentration using logarithmic regression. Therefore, from this numerical model of gelatin matrix, it is possible to estimate exact values extensively.

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A Study on the Bark Percentage of Red Pine (Pinus densiflora S & Z. Produced Kang Won Do) and Larch (Larix KaemPferi Sargent) (강원도(江原道)소나무와 낙엽송(落葉松)의 수피율(樹皮率)에 관(關)한 연구(硏究))

  • Kim, Chang Soo;Lee, Jong Nak
    • Journal of Korean Society of Forest Science
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    • v.6 no.1
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    • pp.1-5
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    • 1967
  • We studied on the bark Percentage of red pine (Pinus denssiflora S & Z) and tarch (Larix Kaemdferi sargent) and obtained the results as follows: (1) For diameter classes from 8 to 38 cm in red pine. the linear equation adopts the relation of the bark percentage to the diameter more accurately than the logarithmic equation. (2) The difference between the regression equation of the bark percentage between red pine and Larch is significant and the correlation cofficient in red Pine is high so that standard error of red Pine is lower than its value of Larch. We established, therefore the tables of bark percentage for each species by applying the following regression equations. red Pine Y=10.08205-0.08794x Larch Y=10.3527-0.17071x.

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