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Carmen Elena Lupu, Sergiu Lupu and Adina Petcu

References [1] Dempster, A.P., Laird, N.M. and Rubin, D.B. (1977). Maximum-likelihood from incomplete data via the em algorithm,, J. Royal Statist. Soc. Ser. B. 39 : 1-38. [2] Feller, W. (1965). An introduction to probability theory and its applications. Vol 1, John Wiley&Sons, New York . [3] Gonzales, L.A.P., Vaduva, I. (2010). Simulation of some mixed lifetime distributions. The 13-rd Conference of Romanian Society of Probability and Statistics, Technical University of Civil Engineering, Bucharest, April, 16-17 . [4] Jose Flores D

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S.O. Pyskunov, Yu.V. Maksimyk and V.V. Valer

1 Introduction Structural elements of responsible objects function often under long-term static or cyclic force loading. The process of creep or fatigue, accompanied by the gradual accumulation of scattered damage, the formation and growth of macroscopic defects (fracture zones) are occurs under such a loading conditions. This problem, similarly as well as other aspects of reliability analysis [ 1 , 2 , 5 ], is very important for a reliable determination of long-term strength and lifetime. A description of above mentioned processes, which took the name

Open access

Irina Băncescu

References [1] Aarset M.V., How to identify a bathtub hazard rate, IEEE Transactions on Reliability, 36, (1987). [2] Akgul F., Frangopol DM, Computational platform for predicting lifetime system reliability pro_tes for di_erent structure types in a network, Jour- nal of Computing in Civil Engineering, 18(2) (2004), 92-104. [3] Andrews D.F., Herzberg A.M., Data: a collection of problems from many fields for the student and research worker, Springer Science Business Me- dia (2012). [4] Arnold B

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Jorge A. Achcar, Emílio A. Coelho-Barros and Josmar Mazucheli

ABSTRACT

We introduce the Weibull distributions in presence of cure fraction, censored data and covariates. Two models are explored in this paper: mixture and non-mixture models. Inferences for the proposed models are obtained under the Bayesian approach, using standard MCMC (Markov Chain Monte Carlo) methods. An illustration of the proposed methodology is given considering a life- time data set.

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Prafulla Kumar Swain, Gurprit Grover and Komal Goel

Abstract

The cure fraction models are generally used to model lifetime data with long term survivors. In a cohort of cancer patients, it has been observed that due to the development of new drugs some patients are cured permanently, and some are not cured. The patients who are cured permanently are called cured or long term survivors while patients who experience the recurrence of the disease are termed as susceptibles or uncured. Thus, the population is divided into two groups: a group of cured individuals and a group of susceptible individuals. The proportion of cured individuals after the treatment is typically known as the cure fraction. In this paper, we have introduced a three parameter Gompertz (viz. scale, shape and acceleration) or generalized Gompertz distribution in the presence of cure fraction, censored data and covariates for estimating the proportion of cure fraction through Bayesian Approach. Inferences are obtained using the standard Markov Chain Monte Carlo technique in openBUGS software.

Open access

Ioana Panait

Cressie and Read case and applications, Proceedings of the Romanian Academy-series A, vol 2- to appear [4] Bălcău C., Constantin D., Panait I. Ioana, Some bounds for the weighted cumulative paired interval entropy, International Journal of Risk Theory, Vol 7 (no.2), 2017 [5] Băncescu I., Comparing the expected system lifetimes of k-out-of-m sys- tems using transmuted-G distributions, Proceedings of the Romanian Academy- to appear (2017). [6] Belis M., Guiaşu S., 1968. A quantitative-qualitative measure of informa- tion in

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Kristīne Šneidere, Nourah Alruwais, Nicholas G. Dowell, Voldemārs Arnis, Jeļena Harlamova, Kārlis Kupčs, Iveta Mintāle, Zane Ulmane, Andra Vanaga, Jeremy C. Young, Jennifer Rusted and Ainārs Stepens

: Evidence for GNG4 and KCNQ2 genes. Amer. J. Alzheimer’s Dis. Oth. Dement., 33 (3), 153–165. Erickson, K. I., Voss, M. W., Shaurya, R., Basak, C., Szabo, A. (2011). Exercise training increases size of hippocampus and improves memory. Proc. Natl. Acad. Sci. Amer ., 108 (7), 3017–3022. Friedenreich, C. M., Courneya, K. S., Bryant, H. E. (1998). The lifetime total physical activity questionnaire: Development and reliability. Med. Sci. Sports Exer., 30 (2), 266–274. Hedden, T., Gabrieli, J. D. E. (2004). Insights into the ageing mind: A view

Open access

Elisabet Wirfält

Abstract

The Malmö Diet Cancer (MDC) group is a population-based cohort (n = 28 098) among Malmö inhabitants, aged 45-73 years at the time of baseline examinations in 1991-1996. Data collection regarding socio-demography, anthropometry and lifestyle was extensive, and included nonfasting blood samples. A high validity diet history was used to determine the usual diet. Information regarding cancer morbidity and mortality from the Swedish Cancer Registry is assessed yearly. Findings support the accepted hypotheses that a lifetime overexposure to sex hormones (modern reproductive patterns) and obesity promote postmenopausal breast cancer. Also, women with high intakes (compared to low intakes) of fibre, folic acid and fermented milk products have lower risk of postmenopausal breast cancer. High intakes of alcohol and energyadjusted fat are associated with increased risk. Also, high intakes of dried soup-sauce-powders and of fried potatoes are associated with increased breast cancer risk. The MDC has two unique assets: the high validity dietary data and the well maintained bio bank. Since a multitude and diverse processes likely contribute to chronic disease the active use of biomarkers has become increasingly important to nutrition epidemiology. Clear information about the diet-breast cancer link is important to many women, because unlike reproductive factors diet is changeable throughout the lifecycle.

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Kristaps Jurjāns, Santa Sabeļnikova, Evija Miglāne, Baiba Luriņa, Oskars Kalējs, Andrejs Millers and Zanda Priede

Anticoagulation and Risk Factors in Atrial Fibrillation (ATRIA) study. J. Amer. Med. Assoc., 285, 2370-2375. Heeringa, J., Van der Kuip, D.A., Hofman, A., Kors, J. A., Van Herpen, G., Stricker, B. H., Stijnen, T., Lip, G. Y., Witteman, J. C. (2006). Prevalence, incidence and lifetime risk of atrial fibrillation: The Rotterdam study. J. Eur. Heart, 27 (8), 949-953. Hobbs, F. R., Taylor, C. J., Jan Geersing, G., Rutten, F. H., Brouwer, J. R. (2015). European Primary Care Cardiovascular Society (EPCCS) consensus guidance on stroke prevention in

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Aldis Strēlnieks, Alberts Bērziņš, Māra Karakone, Irina Pupkeviča, Kristīne Jubele, Maija Vikmane, Sandis Sakne, Oskars Kalējs and Aivars Lejnieks

., 37 , 2893–2962. Kirchhof, P., Monnig, G., Wasmer, K., Heinecke, A., Breithardt, G., Eckardt, L., Bocker, D. (2005) A trial of self-adhesive patch electrodes and hand-held paddle electrodes for external cardioversion of atrial fibrillation (MOBIPAPA). Eur. Heart J. , 26 , 1292–1297. Lloyd-Jones, D. M.,Wang, T. J., Leip, E. P., Larson, M. G., Levy, D., Vasan, R. S., D’Agostino, R. B., Massaro, J. M., Beiser, A., Wolf, P. A., Benjamin, E. J. (2004). Lifetime risk for development of atrial fibrillation: The Framingham Heart Study. Circulation , 110