Parameter estimation for bivariate Weibull distribution using generalized moment method for reliability evaluation

2018 ◽  
Vol 34 (4) ◽  
pp. 631-640 ◽  
Author(s):  
Fuqing Yuan
Keyword(s):  
Parameter Estimation ◽  
Weibull Distribution ◽  
Moment Method ◽  
Reliability Evaluation ◽  
Generalized Moment ◽  
Bivariate Weibull Distribution

Modeling Copper Prices: Ornstein-Uhlenbeck Process and Jump-Diffusions

2012 ◽  
Vol 461 ◽  
pp. 793-796
Author(s):  
Xi Bing Li ◽  
Yu Xi Hu ◽  
Zhen Zhong Zhang ◽  
Xin Ru Liu
Keyword(s):  
Parameter Estimation ◽  
Moment Method ◽  
Futures Market ◽  
Uhlenbeck Process ◽  
Jump Diffusions ◽  
Ornstein Uhlenbeck Process ◽  
Futures Price ◽  
Generalized Moment

In this paper we focus on parameter estimation of the futures price processes with a Ornstein-Uhlenbeck process and jump-diffusions. We use the generalized moment method to derive the OU process. Afterwards, we fit a jump diffusions model to Copper prices from Shanghai Copper futures market.

scholarly journals Reliability-Centered Maintenance: Analyzing Failure in Harvest Sugarcane Machine Using Some Generalizations of the Weibull Distribution

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Pedro L. Ramos ◽  
Diego C. Nascimento ◽  
Camila Cocolo ◽  
Márcio J. Nicola ◽  
Carlos Alonso ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Weibull Distribution ◽  
Cost Savings ◽  
Maintenance Scheduling ◽  
Predictive Analysis ◽  
Main Interest ◽  
Mathematical Background ◽  
Reliability Centered Maintenance ◽  
Best Fit

We considered five generalizations of the standard Weibull distribution to describe the lifetime of two important components of sugarcane harvesting machines. The harvesters considered in the analysis harvest an average of 20 tons of sugarcane per hour and their malfunction may lead to major losses; therefore, an effective maintenance approach is of main interest for cost savings. For the considered distributions, mathematical background is presented. Maximum likelihood is used for parameter estimation. Further, different discrimination procedures were used to obtain the best fit for each component. At the end, we propose a maintenance scheduling for the components of the harvesters using predictive analysis.

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