Search Results - (( data distribution methods algorithm ) OR ( parameters simulation model algorithm ))
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1
Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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2
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
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3
Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data
Published 2016“…A simulation study shows that the slice sampler algorithm provides posterior means with low errors for the parameters along with a high level of stationarity in iteration series. …”
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4
Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. …”
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5
Bayesian inference for the bivariate extreme model
Published 2016“…Using simulation study, the capability of MTM algorithm to analyze the posterior distribution is implement. …”
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6
Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. …”
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7
An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…The main metabolic model of E. coli was used as a benchmark which contained 172 kinetic parameters distributed in five pathways. …”
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8
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We classify the cluster group that exceeds the stopping rule as potential outliers. Model verification of all method and model proposed in this study are examined using the simulation study. …”
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9
Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…The proposed strategy is dependent on modified Zimmermanns approach for handling all inexact operating costs, data capacities, and demand variables. The SD algorithm is employed to balance exploitation and exploration in MSA, thereby resulting in efficient and effective (speed and quality) solution for the APP model. …”
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10
Competing risks for reliability analysis using Cox’s model
Published 2007“…This paper seeks to show that, with a large sample size based on expectation maximization (EM) algorithm, both models give similar results. Design/methodology/approach – The parameters of the models have been estimated by method of maximum likelihood based on EM algorithm. …”
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11
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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12
Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…In general, both methods are performing well for analyzing extreme model but numerical results show that MTM method performs slightly better than MH method in terms of efficiency and convergency to the stationary distribution. …”
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13
Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods
Published 2025“…To validate the clustering model on real data, the Spearman-average algorithm was applied to cluster Juru river basin data based on five water quality parameters. …”
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14
Kalman filter based impedance parameter estimation for transmission line and distribution line
Published 2019“…To demonstrate the efficiency of the new proposed method, a case study of simulated distribution line in UMP is also considered. …”
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15
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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16
Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises
Published 2020“…After it has worked properly, it was applied to model human heart rate data. The results showed that the MCMC algorithm can estimate the parameters of the MA model. …”
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17
Voltage and load profiles estimation of distribution network using independent component analysis / Mashitah Mohd Hussain
Published 2014“…In addition, a real-time load profiles on feeder distribution can be established instead of load modelling technique by using incoming distribution feeder data profiles. …”
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18
PSO modelling and PID controlled of automatic fish feeder system
Published 2020“…The main objective of this study is to improve the performance of fish feeding system by using PID controller through ARX modelling. In this study, raw data at distribution part with speed of 130 rpm, 160 rpm, 190 rpm, 220 rpm and 250 rpm were extracted and used to determine ARX equation parameters as transfer function by using PSO algorithm to optimize ARX model parameter. …”
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19
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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20
Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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