Search Results - (( weibull distribution rate algorithm ) OR ( parametric estimation methods algorithm ))
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An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data.
Published 2011“…In this article, we consider the Bounded Cumulative Hazard (BCH) model that is more appropriate than mixture cure model in case of cancer clinical trials when the population of interest contains long-term survivors or cured. We propose this cure rate model based on the Weibull distribution with interval censored data. …”
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…The major research findings were as follows: 1) the non-parametric and parametric estimation methods using the right and interval censoring types produced highly efficient cure rate parameters when the censoring rate was decreased to the minimum possible; 2) Non-parametric estimation of the cure fraction using interval censored data based on Turnbull estimator resulted in more precise cure fraction than the Kaplan Meier estimator considering the interval midpoint to represent the exact life time; 3) The parametric estimation of the cure fraction based on the exponential distribution and right and interval censoring types produced more consistent estimates than the Weibull distribution especially in case of heavy censoring; 4) Parametric estimation of the cure fraction was more efficient when some covariates had been involved in the analysis than when covariates had been excluded; and 5) the nonparametric estimation method is the viable alternative to the parametric one when the data set contains substantial censored observations while in the case of low censoring the parametric method is more attractive.…”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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Semiparametric estimation with profile algorithm for longitudinal binary data
Published 2013“…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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Variational Bayesian inference for exponentiated Weibull right censored survival data
Published 2023“…The Weibull distribution is on the other hand well-known for modelling monotonic hazard rates. …”
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Cash-flow analysis of a wind turbine operator
Published 2023“…The paper outlines a method to evaluate the distribution of WTG operator's daily cash-flow by developing an algorithm based on Monte-Carlo technique. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Parametric maximum likelihood estimation of cure fraction using interval-censored data
Published 2013“…The parametric maximum likelihood estimation method was used for estimation of the cure fraction based on application of the bounded cumulative hazard (BCH) model to interval-censored data. …”
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…Parametric approaches include linear parametric modelling of the system using recursive least squares (RLS) and genetic algorithms (GAS); and non-parametric approaches include multi-layered perceptron neural networks (MLP-NNs) and adaptive neuro-fuzzy inference systems (ANFIS) are employed. …”
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Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft
Published 2015“…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
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GEE-smoothing spline in semiparametric model with correlated nominal data
Published 2010“…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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Conference or Workshop Item -
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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
Published 2016“…Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. …”
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Semiparametric binary model for clustered survival data
Published 2014“…A backfitting algorithm is used in the derivation of the estimating equation for the parametric and nonparametric components of a semiparametric binary covariate model. …”
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Analysis of the ECG signal using SVD-based parametric modelling technique
Published 2011“…A two-stage procedure is then used to estimate the EDS model parameters. Prony’s algorithm is first used to obtain initial estimates of the model, while the Gauss-Newton method is applied to solve the non-linear least-square optimisation problem. …”
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Proceeding Paper -
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Parametric cure fraction models for interval-censoring with a change-point based on a covariate threshold
Published 2015“…The proposed model has sound motivation in relapse of cancer and can be used in other disease models. The parametric maximum likelihood estimation method is employed to verify the performance of the MCM within the framework of the expectation-maximization (EM) algorithm while the estimation methods for other models are employed in a simpler and straightforward setting. …”
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