• Asian-Australasian Journal of Animal Sciences
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• v.14 no.5
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• pp.597-602
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• 2001

This study was conducted to examine the relationships between the methods used to determine the number of transferable embryos collected per flush and the estimated cumulative genetic improvements in the Japanese Holstein MOET breeding population. Cumulative genetic improvements were predicted by Monte Carlo simulation using three different determination methods (MODEL 1, MODEL 2, and MODEL 3), for calculating the number of embryos collected per flush. Moreover EBVs were estimated including or ignoring coefficients of inbreeding in MME. Inbreeding coefficients were also predicted. The number of transferable embryos was determined using normal, gamma, and Poisson distributions in MODEL 1, gamma and Poisson distributions in MODEL 2, and only the Poisson distribution in MODEL 3. The fitness of MODEL 2 in relation to field data from Hokkaido Japan was the best, and the results for MODEL3 indicated that this model is unsuitable for determining the number of transferable embryos. The largest cumulative genetic improvement (3.11) in the 10th generation was predicted by MODEL 3 and the smallest (2.83) by MODEL 2. Mean coefficients of correlation between the true and estimated breeding values were 0.738, 0.729, and 0.773 in MODELS 1, 2, and 3, respectively. It is suggested that the smallest genetic improvement in MODEL 2 resulted from the smallest correlation coefficient between the true and estimated breeding values. The differences in milk, fat, and protein yields between MODELS 2 and 3 were 182.0, 7.0, and 5.6 kg, respectively, in real units when each trait was independently selected. The inbreeding coefficient was the highest (0.374) in MODEL 2 and the lowest (0.357) in MODEL 3. The effects of different methods for determining the number of transferable embryos per flush on genetic improvements and inbreeding coefficients of the simulated populations were remarkable. The effects of including coefficients of inbreeding in MME, however, were unclear.

• Journal of Food Hygiene and Safety
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• v.19 no.1
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• pp.19-24
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• 2004

Dose-response models in microbial risk assessment can be divided into biologically plausible models and empirical models. Biologically plausible models are formed by the assumptions in dose distribution of microbes, host sensitivity to microbes, and minimal infectious dose of microbes : there are Exponential model and $\beta$-Poisson model, representatively. Empirical models are mainly used to express the toxicity of chemicals : there are Weibull-Gamma model etc. Deviance function (Y) is used to fit available data to dose-response models, and some dose-response models for food-borne pathogens are developed in humans and experimental animals.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5669-5673
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• 2015

Background: Breast cancer is the most prevalent kind of cancer among women in Iran. Regarding the importance of cancer prevention and considerable variation of breast cancer incidence in different parts of the country, it is necessary to recognize regions with high incidence of breast cancer and evaluate the role of potential risk factors by use of advanced statistical models. The present study focussed on incidence of breast cancer in Iran at the province level and also explored the impact of some prominent covariates using Bayesian models. Materials and Methods: All patients diagnosed with breast cancer in Iran from 2005 to 2008 were included in the study. Smoking, fruit and vegetable intake, physical activity, obesity and the Human Development Index (HDI), measured at the province level, were considered as potential modulating factors. Gamma-Poisson, log normal and BYM models were used to estimate the relative risk of breast cancer in this ecological investigation with and without adjustment for the covariates. Results: The unadjusted BYM model had the best fit among applied models. Without adjustment, Isfahan, Yazd, and Tehran had the highest incidences and Sistan- Baluchestan and Chaharmahal-Bakhtiari had the lowest. With the adjusted model, Khorasan-Razavi, Lorestan and Hamedan had the highest and Ardebil and Kohgiluyeh-Boyerahmad the lowest incidences. A significantly direct association was found between breast cancer incidence and HDI. Conclusions: BYM model has better fit, because it contains parameters that allow including effects from neighbors. Since HDI is a significant variable, it is also recommended that HDI should be considered in future investigations. This study showed that Yazd, Isfahan and Tehran provinces feature the highest crude incidences of breast cancer.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.27-36
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• 2005

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates Per fault. This Paper Proposes reliability model using the generalized gamma distribution, which can capture the monotonic increasing(or monotonic decreasing) nature of the failure occurrence rate per fault. Equations to estimate the parameters of the generalized gamma finite failure NHPP model based on failure data collected in the form of interfailure times are developed. For the sake of proposing shape parameter of the generalized gamma distribution, used to the special pattern. Data set, where the underlying failure process could not be adequately described by the knowing models, which motivated the development of the gamma or Weibull model. Analysis of failure data set for the generalized gamma modell, using arithmetic and Laplace trend tests . goodness-of-fit test, bias tests is presented.

• Journal of Applied Reliability
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• v.7 no.1
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• pp.13-22
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• 2007

A preventive maintenance model, caller FNBM (${\alpha},{\delta},{\gamma}$) model, is proposed to decide an optimal repair number under achieved availability requirements (r) along with taking two types of failures (repairable or irrepairable) into account. In this model, the current system is replaced by a new one in case when it doesn't meet the achieved availability requirement, even though it is repairable failure; Othewise it is replaced in time of the first irrepairable failure. Assumed that the j-th failure is repairable with probability ${\alpha}_j$ minimal repairs are allowed for repairable failure between replacements. Expected cost rate for preventive maintenance model is developed using NHPP (Non - Homogeneous Poisson Process) in order to de term in the optimal number $n^*$, also numerical examples are shown in order to explain the proposed model. Since the proposed FNBM (${\alpha},{\delta},{\gamma}$) model includes Park FNBM model (1979) and Nakagawa FNBM (p) model (1983) m this proposed model is thought to be better than previous model, especially for weapon system which requires availability as primary parameter.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.95-102
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• 2017

Gamma generalized linear models have received less attention than Poisson and binomial generalized linear models. Therefore, many old-established statistical techniques are still used in gamma generalized linear models. In particular, existing literature and textbooks still use approximate estimates for the dispersion parameter. In this paper we study the efficiency of various dispersion parameter estimators in gamma generalized linear models and perform numerical simulations. Numerical studies show that the maximum likelihood estimator and Cox-Reid adjusted maximum likelihood estimator are recommended and that approximate estimates should be avoided in practice.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1017-1026
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• 2005

We consider the problem of modeling count data where the observation period is determined by the survival time of the individual under study. We assume random effects or frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect, the death times follow a Weibull distribution with a rate that depends on some covariates. For the counts, given the random effect, a Poisson process is assumed with the intensity depending on time and the covariates. A gamma model is assumed for the random effect. Maximum likelihood estimators of the model parameters are obtained. The model is applied to data set of patients with breast cancer who received a bone marrow transplant. A model for the time to death and the number of supportive transfusions a patient received is constructed and consequences of the model are examined.

• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.89-98
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• 2008

A preventive maintenance model, caller FNBM($\alpha$, $\delta$, $\gamma$)model, is proposed to decide an optimal repair number under achieved availability requirements(r) along with taking two types of failures (repairable or irrepairable) into account. In this model, the current system is replaced by a new one in case when it doesn't meet the achieved availability requirement, even though it is repairable failure; Otherwise it is replaced in time of the first irrepairable failure. Assumed that the j-th failure is repairable with probability ${\alpha}_j$ minimal repairs are allowed for repairable failure between replacements. Expected cost rate for preventive maintenance model is developed using NHPP(Non-Homogeneous Poisson Process) in order to determine the optimal number $n^*$, also numerical examples are shown in order to explain the proposed model. Since the proposed FNBM($\alpha$, $\delta$, $\gamma$)model includes Park FNBM model(1979) and Nakagawa FNBM(p)model(1983) this proposed model is thought to be better than previous model, especially for weapon system which requires availability as primary parameter.

• Journal of Korean Society for Quality Management
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• v.26 no.4
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• pp.111-123
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• 1998

We consider the problem of modeling count data where the observation period is determined by the life time of the system under study. We assume random effects or a frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect or a frailty, the death times follow a Weibull distribution with a hazard rate. For the counts, given a frailty, a Poisson process is assumed with the intensity depending on time. A gamma distribution is assumed for the frailty model. Maximum likelihood estimators of the model parameters are obtained. A model for the time to death and the number of failures system received is constructed and consequences of the model are examined.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3816-3823
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• 2021

The mechanical features evaluated theoretically using Makishima-Mackenzie's model for glasses xBaO-(50-x) PbO-50P₂O₅ where x = 0, 5, 10, 15, 20, 30, 40, and 50 mol%. Wherefore, the elastic characteristics; Young's, bulk, shear, and longitudinal modulus calculated. The obtained result showed an increase in the calculated values of elastic moduli with the replacement of the PbO by BaO contents. Moreover, the Poisson ratio, micro-hardness, and the softening temperature calculated for the investigated glasses. Besides, gamma and neutron shielding ability evaluated for the barium doped lead phosphate glasses. Monte Caro code (MCNP-5) and the Phy-X/PSD program applied to estimate the mass attenuation coefficient of the studied glasses. The decrease in the PbO ratio has a negative effect on the MAC. The highest MAC decreased from 65.896 cm²/g to 32.711 cm²/g at 0.015 MeV for BPP0 and BPP7, respectively. The calculated values of EBF and EABF showed that replacement of PbO with BaO contents in the studied BPP glasses helps to reduce the number of photons accumulated inside the studied BPP glasses.