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An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data.
Published 2011“…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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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…From the simulation study for this particular case, we can conclude that Weibull distribution describes well the nature of the model concerned as compared to the exponential distribution in terms of the mean value of parameter estimates, bias, and the root means square error. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…In this method, firstly, Weibull density function is utilized to model the wind speed and then several methods are applied to estimate the parameters of the wind speed distribution. …”
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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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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Analysis results present Weibull Distribution model is the best fitted model. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Analysis results present Weibull Distribution model is the best fitted model. …”
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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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Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior
Published 2013“…For the Weibull model with right censoring and unknown shape, the full conditional distribution for the scale and shape parameters are obtained via Gibbs sampling and Metropolis-Hastings algorithm from which the survival function and hazard function are estimated. …”
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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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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 Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia
Published 2023Conference Paper -
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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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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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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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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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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This study begins by proposing a robust technique for estimating the slope parameter in LFRM. In particular, the focus is on the non-parametric estimation of the slope parameter and the robustness of this technique is compared with the maximum likelihood estimation and the Al-Nasser and Ebrahem (2005) method. …”
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