• Title, Summary, Keyword: lognormal model

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A Robust Estimation for the Composite Lognormal-Pareto Model

  • Pak, Ro Jin
    • Communications for Statistical Applications and Methods
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    • v.20 no.4
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    • pp.311-319
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    • 2013
  • Cooray and Ananda (2005) proposed a composite lognormal-Pareto model to analyze loss payment data in the actuarial and insurance industries. Their model is based on a lognormal density up to an unknown threshold value and a two-parameter Pareto density. In this paper, we implement the minimum density power divergence estimation for the composite lognormal-Pareto density. We compare the performances of the minimum density power divergence estimator (MDPDE) and the maximum likelihood estimator (MLE) by simulations and an example. The minimum density power divergence estimator performs reasonably well against various violations in the distribution. The minimum density power divergence estimator better fits small observations and better resists against extraordinary large observations than the maximum likelihood estimator.

로그분포모형을 이용한 토양입도분포로부터의 불포화수리전도도 추정

  • 황상일
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • pp.99-101
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    • 2003
  • Unsaturated hydraulic conductivity models have been widely used for the numerical modeling of water flow and contaminant transport in soils. In this study, a simple hydraulic conductivity model is developed by using information of particle-size distribution from the lognormal distribution model and its results are compared with those from the Kosugi-Mualem (KM) model. The accuracy of the proposed model is verified for observed data chosen from the international UNSODA database. Results showed that the proposed model produces adequate predictions of hydraulic conductivities. Performance of this model is generally better than the KM function.

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Bayesian Hypothesis Testing for Two Lognormal Variances with the Bayes Factors

  • Moon, Gyoung-Ae
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.1119-1128
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    • 2005
  • The Bayes factors with improper noninformative priors are defined only up to arbitrary constants. So it is known that Bayes factors are not well defined due to this arbitrariness in Bayesian hypothesis testing and model selections. The intrinsic Bayes factor and the fractional Bayes factor have been used to overcome this problem. In this paper, we suggest a Bayesian hypothesis testing based on the intrinsic Bayes factor and the fractional Bayes factor for the comparison of two lognormal variances. Using the proposed two Bayes factors, we demonstrate our results with some examples.

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A Study on the Simulation of Monthly Discharge by Markov Model (Markov모형에 의한 월유출량의 모의발생에 관한 연구)

  • 이순혁;홍성표
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.31 no.4
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    • pp.31-49
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    • 1989
  • It is of the most urgent necessity to get hydrological time series of long duration for the establishment of rational design and operation criterion for the Agricultural hydraulic structures. This study was conducted to select best fitted frequency distribution for the monthly runoff and to simulate long series of generated flows by multi-season first order Markov model with comparison of statistical parameters which are derivated from observed and sy- nthetic flows in the five watersheds along Geum river basin. The results summarized through this study are as follows. 1. Both two parameter gamma and two parameter lognormal distribution were judged to be as good fitted distributions for monthly discharge by Kolmogorov-Smirnov method for goodness of fit test in all watersheds. 2. Statistical parameters were obtained from synthetic flows simulated by two parameter gamma distribution were closer to the results from observed flows than those of two para- meter lognormal distribution in all watersheds. 3. In general, fluctuation for the coefficient of variation based on two parameter gamma distribution was shown as more good agreement with the observed flow than that of two parameter lognormal distribution. Especially, coefficient of variation based on two parameter lognormal distribution was quite closer to that of observed flow during June and August in all years. 4. Monthly synthetic flows based on two parameter gamma distribution are considered to give more reasonably good results than those of two parameter lognormal distribution in the multi-season first order Markov model in all watersheds. 5. Synthetic monthly flows with 100 years for eack watershed were sjmulated by multi- season first order Markov model based on two parameter gamma distribution which is ack- nowledged to fit the actual distribution of monthly discharges of watersheds. Simulated sy- nthetic monthly flows may be considered to be contributed to the long series of discharges as an input data for the development of water resources. 6. It is to be desired that generation technique of synthetic flow in this study would be compared with other simulation techniques for the objective time series.

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Estimation on composite lognormal-Pareto distribution based on doubly censored samples (결합 로그노말-파레토 분포에서 추출된 양쪽 중도 절단된 표본을 이용한 모수추정)

  • Lee, Kwang-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.2
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    • pp.171-177
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    • 2011
  • With the development of the actuarial and insurance industries, the distributions of the insurance payments data are deeply studied by many authors. It is known that theses types of distribution are very highly positively skewed and have a long thick upper tail such as Pareto or lognormal distribution. In 2005, Cooray and Ananda proposed a new model which is composed lognormal distribution and Pareto distribution. They said it as composite lognormal-Preto distribution. They showed that the proposed distribution was better fitted than lognormal or Pareto distribution. On the other hand many agreements about the insurance payment have some options for a trivially small payment or extremely large one because of the limits of total payment. Appling these cases, in this paper we consider the parameter estimation on the composite lognormal-Pareto distribution based on doubly censored samples.

Estimation of Water Retention Characteristics Using Lognormal Distribution Model (로그분포모형을 이용한 토양수분특성 추정)

  • Sang Il Hwang
    • Journal of Soil and Groundwater Environment
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    • v.8 no.4
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    • pp.21-26
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    • 2003
  • Hwang and Powers (2003) developed a simple model for estimating water retention characteristic (WRC) directly from particle-size distribution (PSD) data, by applying a lognormal distribution law to both PSD and pore-size distribution. The objective of this work was to determine if the performance of the model developed by Hwang and Powers (2003) would be affected by soil texture. The results of this research proved that the performance of the model was indeed affected by soil texture. In particular, its performance diminished with increases in the fine particle fractions. Also, the nonlinear model, which assumes a nonlinear relation between particle-size and pore-size, performed better than the linear model, regardless of soil texture classes.

Applying Conventional and Saturated Generalized Gamma Distributions in Parametric Survival Analysis of Breast Cancer

  • Yavari, Parvin;Abadi, Alireza;Amanpour, Farzaneh;Bajdik, Chris
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.5
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    • pp.1829-1831
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    • 2012
  • Background: The generalized gamma distribution statistics constitute an extensive family that contains nearly all of the most commonly used distributions including the exponential, Weibull and log normal. A saturated version of the model allows covariates having effects through all the parameters of survival time distribution. Accelerated failure-time models assume that only one parameter of the distribution depends on the covariates. Methods: We fitted both the conventional GG model and the saturated form for each of its members including the Weibull and lognormal distribution; and compared them using likelihood ratios. To compare the selected parameter distribution with log logistic distribution which is a famous distribution in survival analysis that is not included in generalized gamma family, we used the Akaike information criterion (AIC; r=l(b)-2p). All models were fitted using data for 369 women age 50 years or more, diagnosed with stage IV breast cancer in BC during 1990-1999 and followed to 2010. Results: In both conventional and saturated parametric models, the lognormal was the best candidate among the GG family members; also, the lognormal fitted better than log-logistic distribution. By the conventional GG model, the variables "surgery", "radiotherapy", "hormone therapy", "erposneg" and interaction between "hormone therapy" and "erposneg" are significant. In the AFT model, we estimated the relative time for these variables. By the saturated GG model, similar significant variables are selected. Estimating the relative times in different percentiles of extended model illustrate the pattern in which the relative survival time change during the time. Conclusions: The advantage of using the generalized gamma distribution is that it facilitates estimating a model with improved fit over the standard Weibull or lognormal distributions. Alternatively, the generalized F family of distributions might be considered, of which the generalized gamma distribution is a member and also includes the commonly used log-logistic distribution.

Gap-Acceptance Behavior Model of Left-Turn Drivers. (좌회전운전자의 문격수낙행태 모형)

  • 김경환
    • Journal of Korean Society of Transportation
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    • v.4 no.2
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    • pp.3-14
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    • 1986
  • This study was undertaken to develop the gap acceptance model of left-turn drivers on the major road at intersections. Typical unsignalized intersections on the two-lane and four-lane streets in Masan City were selected for the study intersection. For the gap distribution model, the lognormal, negative exponential, shifted negative exponential, and Gamma distributions were tested using the x2 and K-S tests. Based on the results for both streets, it was concluded that among the distributions tested the lognormal distribution represented the gap distribution best, followed by the shifted negative exponential distribution. Stochastic models of the gap-acceptance behavior of left-turn drivers on the major road at unsignalized intersections were programmed using SLAM Ⅱ, a simulation computer language. A stochastic model was selected for the gap-acceptance behavior to compare the results of the simulation with the observed data. The model assumes that a fixed critical acceptance gap is assigned to each left-turn driver based on a normal distribution and the gap distribution of the opposing traffic stream follows the shifted negative exponential distribution.

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Statistical Analysis of Degradation Data under a Random Coefficient Rate Model (확률계수 열화율 모형하에서 열화자료의 통계적 분석)

  • Seo, Sun-Keun;Lee, Su-Jin;Cho, You-Hee
    • Journal of the Korean Society for Quality Management
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    • v.34 no.3
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    • pp.19-30
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    • 2006
  • For highly reliable products, it is difficult to assess the lifetime of the products with traditional life tests. Accordingly, a recent approach is to observe the performance degradation of product during the test rather than regular failure time. This study compares performances of three methods(i.e. the approximation, analytical and numerical methods) to estimate the parameters and quantiles of the lifetime when the time-to-failure distribution follows Weibull and lognormal distributions under a random coefficient degradation rate model. Numerical experiments are also conducted to investigate the effects of model error such as measurements in a random coefficient model.

An Economic Design of Reliability Demonstration Test for Product with Lognormal lifetime distribution (수명이 대수정규분포를 따르는 제품에 대한 경제적인 신뢰성 입증시험 설계)

  • Kwon, Young-Il
    • Journal of Applied Reliability
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    • v.12 no.1
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    • pp.47-56
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    • 2012
  • Reliability demonstration tests with zero-failure acceptance criterion are most commonly used in the field of reliability application since they require fewer test samples and less test time compared to other test methods that guarantee the same reliability with a given confidence level. For products with lognormal lifetime distribution, an economic zero-failure test plan is developed that minimizes the total cost related to perform a life test to guarantee a specified reliability of a product with a given confidence level. A numerical example is provided to illustrate the use of the proposed test plan.