scholarly journals The Smallest Probability Interval a Sequence Is Random for: A Study for Six Types of Randomness

2021 ◽  
pp. 442-454
Author(s):  
Floris Persiau ◽  
Jasper De Bock ◽  
Gert de Cooman
Keyword(s):  
Author(s):  
Guo Yu ◽  
Haitao Li ◽  
Yanru Chen ◽  
Linqing Liu ◽  
Chenyu Wang ◽  
...  

AbstractQuantifying natural gas production risk can help guide natural gas exploration and development in Carboniferous gas reservoirs. In this study, the Monte Carlo probability method is used to obtain the probability distribution and growth curve of each production risk factor and production in a Carboniferous gas reservoir in eastern Sichuan. In addition, the fuzzy comprehensive evaluation method is used to conduct the sensitivity analysis of the risk factors, and the natural gas production and realization probability under different risk factors are obtained. The research results show that: (1) the risk factor–production growth curve and probability distribution are calculated by the Monte Carlo probability method. The average annual production under the stable production stage under different realization probabilities is obtained. The maximum probability range of annual production is $$\left( {43.43 - 126.35} \right) \times 10^{8} {\text{m}}^{3} /{\text{year}}$$ 43.43 - 126.35 × 10 8 m 3 / year , and the probability range is 14.59–92.88%. (2) The risk factor sensitivity analysis is significantly affected by the probability interval. In the entire probability interval, the more sensitive risk factors are the average production of the kilometer-deep well (D) and the production rate in the stable production stage (A). During the exploration and development of natural gas, these two risk factors can be adjusted to increase production.


2015 ◽  
Vol 12 (04) ◽  
pp. 1540006 ◽  
Author(s):  
C. Jiang ◽  
J. Zheng ◽  
B. Y. Ni ◽  
X. Han

This paper proposes a probability-interval mixed uncertainty model considering parametric correlations and a corresponding structural reliability analysis method. First of all, we introduce the sample correlation coefficients to express the correlations between different kinds of uncertain variables including probability and interval variables. Then dependent parameters are transformed into independent ones through a matrix transformation. A reliability analysis model is put forward, and an efficient method is built to obtain the reliability index or failure probability interval of the structure. Finally, four numerical examples are provided to verify the validity of the method.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 51556-51565 ◽  
Author(s):  
Xiyun Yang ◽  
Xue Ma ◽  
Ning Kang ◽  
Mierzhati Maihemuti

2020 ◽  
Vol 84 (1/2/3/4) ◽  
pp. 238
Author(s):  
Hongjuan Hou ◽  
Guohua Cui ◽  
Haimiao Wu ◽  
Peng Chen

1999 ◽  
Vol 17 (2) ◽  
pp. 494-494 ◽  
Author(s):  
Victor R. Grann ◽  
William Whang ◽  
Judith S. Jacobson ◽  
Daniel F. Heitjan ◽  
Karen H. Antman ◽  
...  

PURPOSE: To determine the survival benefit and cost-effectiveness of screening Ashkenazi Jewish women for three specific BRCA1/2 gene mutations. METHODS: We used a Markov model and Monte Carlo analysis to estimate the survival benefit and cost-effectiveness of screening for three specific mutations in a population in which their prevalence is 2.5% and the associated cancer risks are 56% for breast cancer and 16% for ovarian cancer. We assumed that the sensitivity and specificity of the test were 98% and 99%, respectively, that bilateral prophylactic oophorectomy would reduce ovarian cancer risk by 45%, and that bilateral prophylactic mastectomy would reduce breast cancer risk by 90%. We used Medicare payment data for treatment costs and Surveillance, Epidemiology, and End Results data for cancer survival. RESULTS: Our model suggests that genetic screening of this population could prolong average nondiscounted survival by 38 days (95% probability interval, 22 to 57 days) for combined surgery, 33 days (95% probability interval, 18 to 43 days) for mastectomy, 11 days (95% probability interval, 4 to 25 days) for oophorectomy, and 6 days (95% probability interval, 3 to 8 days) for surveillance. The respective cost-effectiveness ratios per life-year saved, with a discount rate of 3%, are $20,717, $29,970, $72,780, and $134,273. CONCLUSION: In this Ashkenazi Jewish population, with a high prevalence of BRCA1/2 mutations, genetic screening may significantly increase average survival and, depending on costs and screening/treatment strategies, may be cost-effective by the standards of accepted cancer screening tests. According to our model, screening is cost-effective only if all women who test positive undergo prophylactic surgery. These estimates require confirmation through prospective observational studies and clinical trials.


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