SURVIVAL COPULA PARAMETERS ESTIMATION FOR ARCHIMEDEAN FAMILY UNDER SINGLY CENSORING

2021 ◽  
Vol 10 (6) ◽  
pp. 2847-2864
Author(s):  
N. Idiou ◽  
F. Benatia
Keyword(s):  
Diabetic Retinopathy ◽  
Simulation Study ◽  
Estimation Method ◽  
Relative Bias ◽  
Parameters Estimation ◽  
Parametric Estimation ◽  
Lifetime Data ◽  
Archimedean Copulas ◽  
Theoretical Results ◽  
Survival Copula

Given $(Z_{i},\delta _{i})=\left\{ \min (T_{i},C_{i}),I_{(T_{i}<C_{i})_{i=1,2}}\right\} ,$ as dependent or independent right-censored variables, general formulas are proven for a semi-parametric estimation of the proposed method. As a logical continuation of results established by N.IDIOU et al 2021 \cite{ref16}, a new estimator of $\tilde{C}$ is proposed by considering that the underlying copula is Archimedean, under singly censoring data. As an application, two Archimedean copulas models have been chosen to illustrate our theoretical results. A simulation study follows, which sheds light on the behavior of the process estimation method shown that the proposed estimator performs well in terms of relative bias and RMSE. The methodology of the proposed estimator is also illustrated by using lifetime data from the Diabetic Retinopathy Study, where its efficiency and robustness are observed.

scholarly journals New class of Lindley distributions: properties and applications

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Duha Hamed ◽  
Ahmad Alzaghal
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Simulation Study ◽  
Likelihood Estimation ◽  
Statistical Properties ◽  
Data Sets ◽  
Lifetime Data ◽  
Unknown Parameters ◽  
Lindley Distribution ◽  
New Class

AbstractA new generalized class of Lindley distribution is introduced in this paper. This new class is called the T-Lindley{Y} class of distributions, and it is generated by using the quantile functions of uniform, exponential, Weibull, log-logistic, logistic and Cauchy distributions. The statistical properties including the modes, moments and Shannon’s entropy are discussed. Three new generalized Lindley distributions are investigated in more details. For estimating the unknown parameters, the maximum likelihood estimation has been used and a simulation study was carried out. Lastly, the usefulness of this new proposed class in fitting lifetime data is illustrated using four different data sets. In the application section, the strength of members of the T-Lindley{Y} class in modeling both unimodal as well as bimodal data sets is presented. A member of the T-Lindley{Y} class of distributions outperformed other known distributions in modeling unimodal and bimodal lifetime data sets.

scholarly journals Computer Modelling For 4-Stroke Direct Injection Diesel Engine

2008 ◽  
Vol 33-37 ◽  
pp. 801-806
Author(s):  
Abdul Rahim Ismail ◽  
Rosli Abu Bakar ◽  
Semin Ali ◽  
Ismail Ali
Keyword(s):  
Diesel Engine ◽  
Simulation Study ◽  
Engine Speed ◽  
Computer Modelling ◽  
Direct Injection ◽  
One Dimension ◽  
Effective Pressure ◽  
Operational Parameters ◽  
Direct Injection Diesel Engine ◽  
Theoretical Results

Study on computational modeling of 4-stroke single cylinder direct injection diesel engine is presented. The engine with known specification is being modeled using one dimension CFD GT-Power software. The operational parameters of the engine such as power, torque, specific fuel consumption and mean effective pressure which are dependent to engine speed are being discussed. The results from the simulation study are compared with the theoretical results to get the true trend of the results.

scholarly journals Experimental Evaluation of PSO Based Transfer Learning Method for Meteorological Visibility Estimation

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 828
Author(s):  
Wai Lun Lo ◽  
Henry Shu Hung Chung ◽  
Hong Fu
Keyword(s):  
Transfer Learning ◽  
Experimental Evaluation ◽  
Estimation Method ◽  
Image Features ◽  
Parameters Estimation ◽  
Image Feature ◽  
Support Vector ◽  
Learning Method ◽  
Feature Vectors ◽  
Visibility Estimation

Estimation of Meteorological visibility from image characteristics is a challenging problem in the research of meteorological parameters estimation. Meteorological visibility can be used to indicate the weather transparency and this indicator is important for transport safety. This paper summarizes the outcomes of the experimental evaluation of a Particle Swarm Optimization (PSO) based transfer learning method for meteorological visibility estimation method. This paper proposes a modified approach of the transfer learning method for visibility estimation by using PSO feature selection. Image data are collected at fixed location with fixed viewing angle. The database images were gone through a pre-processing step of gray-averaging so as to provide information of static landmark objects for automatic extraction of effective regions from images. Effective regions are then extracted from image database and the image features are then extracted from the Neural Network. Subset of Image features are selected based on the Particle Swarming Optimization (PSO) methods to obtain the image feature vectors for each effective sub-region. The image feature vectors are then used to estimate the visibilities of the images by using the Multiple Support Vector Regression (SVR) models. Experimental results show that the proposed method can give an accuracy more than 90% for visibility estimation and the proposed method is effective and robust.

Reliability assessment of offshore dynamic scour protections using copulas

2018 ◽  
Vol 43 (5) ◽  
pp. 506-538 ◽  
Author(s):  
T Fazeres-Ferradosa ◽  
F Taveira-Pinto ◽  
X Romão ◽  
MT Reis ◽  
L das Neves
Keyword(s):  
Wind Farm ◽  
Estimation Method ◽  
Information Criterion ◽  
Probability Of Failure ◽  
Parametric Estimation ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Spectral Parameters ◽  
Peak Period ◽  
Kendall’S Τ

This article presents a methodology to assess the reliability of dynamic scour protections used to protect offshore wind turbine foundations. The computed probabilities of failure are based on a dataset of 124 months of hindcast data from the Horns Rev 3 offshore wind farm. Copula-based models are used to obtain the joint distribution function of the significant wave height and spectral peak period and to obtain the probability of failure of scour protections. The sensitivity of the probability of failure to each model is addressed. The influence of the duration of the waves’ time series is also studied. A sensitivity analysis of the probability of failure to physical constraints, such as the water depth, current’s velocity or the mean diameter of the armour units, is performed. The results show that probability of failure is dependent on the copula used to model the spectral parameters and the associated value of Kendall’s τ. It is shown that the copula presenting the best values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) did not lead to the probabilities of failure that are closer to the non-parametric estimation, obtained by means of the bivariate version of the Kernel density estimation method. The application to the case study led to annual probabilities of failure, which are comparable with the values applied for other offshore components, according to the current offshore wind industry standards.

scholarly journals Reducing of noise structure influence on an accuracy of a desired signal extraction

2018 ◽  
Vol 15 (3) ◽  
pp. 365-370 ◽  
Author(s):  
Vladimir Marchuk
Keyword(s):  
Signal Processing ◽  
Mathematical Expectation ◽  
Random Processes ◽  
Parameters Estimation ◽  
Signal Extraction ◽  
Scientific Contribution ◽  
Noise Component ◽  
Component Structure ◽  
Noise Structure ◽  
Theoretical Results

In the paper, the issues regarding the analysis of the noise component structure are addressed and methods for reducing the error in estimating of the mathematical expectation of the noise component are proposed. The use of the proposed method of ?noise purification? makes possibility to reduce the error introduced by the noise structure when estimating the mathematical expectation and dispersion of the noise component during research. The main scientific contribution in this paper in accuracy increasing of random processes parameters estimation. These theoretical results can be applied in different spheres of data analyzing and signal processing when random processes have some structure.

scholarly journals A parameter estimation method for fluorescence lifetime data

2015 ◽  
Vol 8 (1) ◽  
Author(s):  
Daniel Sewell ◽  
Hajin Kim ◽  
Taekjip Ha ◽  
Ping Ma
Keyword(s):  
Parameter Estimation ◽  
Fluorescence Lifetime ◽  
Estimation Method ◽  
Lifetime Data ◽  
Parameter Estimation Method

Time and Price Dependent Demand with Varying Holding Cost Inventory Model for Deteriorating Items

2013 ◽  
Vol 4 (4) ◽  
pp. 75-95 ◽  
Author(s):  
Diwakar Shukla ◽  
Uttam Kumar Khedlekar ◽  
Raghovendra Pratap Singh Chandel
Keyword(s):  
Simulation Study ◽  
Demand Function ◽  
Inventory Model ◽  
Time Parameter ◽  
Suggested Model ◽  
Open Problems ◽  
Holding Cost ◽  
Theoretical Results ◽  
Dependent Demand ◽  
Better Than

This paper presents an inventory model considering the demand as a parametric dependent linear function of time and price both. The coefficient of time-parameter and coefficient of price-parameter are examined simultaneously and proved that time is dominating variable over price in terms of earning more profit. It is also proved that deterioration of item in the inventory is one of the most sensitive parameter to look into besides many others. The robustness of the suggested model is examined using variations in the input parameters and ranges are specified on which the model is robust on most of occasions and profit is optimal. Two kinds of doubly-demand function strategies are examined and mutually compared in view of the two different cases. Second strategy found better than first. Holding cost is treated as a variable. Theoretical results are supported by numerical based simulation study with robustness. Some recommendations are given at the end for the inventory managers and also open problems are discussed for researchers. This model is more realistic than considered by earlier author.

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