Search Results - (( data estimation using algorithm ) OR ( data distribution function algorithm ))

Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari by Nawwal , Ahmad Bukhari

“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

“…Two simulation studies have shown the performance of the peaks over given threshold (POT) and GPD density function on various simulated data sets. The results were compared with another commonly used Markov chain Monte Carlo (MCMC) technique called Metropolis-Hastings algorithm. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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Locating fault using voltage sags profile for underground distribution system by Mokhlis, Hazlie, Li, H.Y., Bakar, A.H.A., Mohamad, H.

“…This paper presents an alternative fault location algorithm to estimate short-circuit faults location in electrical distribution networks using only voltage sags data. …”
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Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications by Hassan, Amal Soliman, Elsherpieny, Elsayed Ahmed, Mohamed, Rokaya Elmorsy

“…This study estimated the Rényi and q-entropies of a power-function distribution in the presence of s outliers using classical and Bayesian procedures. …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior by Ahmed, Al Omari Mohammed

“…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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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

“…In this case, the estimation was developed based on the exponential and Weibull distributions using the right and interval censoring types; and 2) when covariates were incorporated into the analysis through the scaleparameter of the exponential distribution only using the same types of data censoring. …”
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Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

“…The exponential, Weibull, log-logistic and lognormal distributions represent the class of light and heavy-tailed distributions that are often used in modelling time-to-event data. …”
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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

“…K-distribution is known as the best fit probability density function for the radar sea clutter. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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Turnbull versus Kaplan-Meier estimators of cure rate estimation using interval censored data by Aljawadi, Bader Ahmad I., Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

“…This study deals with the analysis of the cure rate estimation based on the Bounded Cumulative Hazard (BCH) model using interval censored data, given that the exact distribution of the data set is unknown. …”
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Robust Kernel Density Function Estimation by Dadkhah, Kourosh

“…The classical kernel density estimation technique is the commonly used method to estimate the density function. …”
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

“…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter by Solouk, Vahid, Taghizadeh, Hamid, Moghanjoughi, Ayyoub Akbari, Razm, S. K.

“…The proposed algorithms provide precise state estimates in a moment as global state estimates using various updates at each step. …”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

“…A generated data where the failure times are taken as exponentially distributed are used to further compare these two parametric models. …”
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Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat by Yuliant, Sibaroni, Sri Suryani, Prasetiyowati, Iqbal Bahari, Sudrajat

“…In this study, the problem of determination dengue disease factors was modeled using a neural network. The activation function in this neural network model then estimated using genetic algorithms. …”
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Rank regression for modeling bus dwell time in the presence of censored observations by Karimi, Mostafa, Ibrahim, Noor Akma

“…A resampling technique is used for estimating the distribution of the rank estimator through its empirical distribution. …”
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