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1
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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2
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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3
Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…Secondly, a new formula representing frequency distribution of the turbine power is derived. …”
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4
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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5
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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6
Non-parametric maximum likelihood estimation of cure fraction for interval survival data.
Published 2011“…We implement the Turnbull algorithm for the survival function estimation using EM algorithm. …”
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7
Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment
Published 2011“…For this purpose, the most probable location of incoming instance for each class is estimated. Then, an optimal transformation matrix is computed by maximizing the information gain at the estimated points. …”
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8
Detection of multiple outliners in linear regression using nonparametric methods
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9
Missing value estimation methods for data in linear functional relationship model
Published 2017“…In this paper, two modern imputing approaches namely expectation-maximization (EM) and expectation-maximization with bootstrapping (EMB) are proposed in this paper for two kinds of linear functional relationship (LFRM) models, namely LFRM1 for full model and LFRM2 for linear functional relationship model when slope parameter is estimated using a nonparametric approach. The performance of EM and EMB are measured using mean absolute error, root-mean-square error and estimated bias. …”
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…Then, a series of simulation studies was conducted to evaluate the performance of the proposed estimation approaches. This research investigated the non-parametric maximum likelihood estimation method for cure rate estimation by considering two common estimators for the survival function: 1) The Kaplan Meier (KM) estimator, which is suitable for the right censoring case; and 2) The Turnbull Estimator, which is suitable for the interval type of data censoring. …”
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12
System Identification of XY Table ballscrew drive using parametric and non parametric frequency domain estimation via deterministic approach
Published 2012“…Both parametric and nonparametric procedure. In addition, comparison of estimated model transfer function obtained via non-linear least square (NLLS) and Linear least square estimator algorithm were also being addressed. …”
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13
Ancestral dynamic voting algorithm for mutual exclusion in partitioned distributed systems
Published 2013“…In this study, a new dynamic algorithm is presented as a solution for mutual exclusion in partitioned distributed systems. …”
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A new technique for the reconfiguration of radial distribution network for loss minimization
Published 2014“…In this paper, a new technique called as Improved Genetic Algorithm (IGA) for reconfiguring distribution network simultaneously implemented with the placement of small scale power generation or Distributed Generation (DG) is presented. …”
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15
A new efficient checkpointing algorithm for distributed mobile computing
Published 2015“…Considering this issue, the contribution in this paper is a proposal of a new checkpointing algorithm suitable for mobile computing systems. …”
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Evaluation of Different Horizon Lengths in Single-agent Finite Impulse Response Optimizer
Published 2019“…In a real UFIR filter, the horizon length, N plays an important role to obtain the optimal estimation. In SAFIRO, N represents the repetition number of estimation part that needs to be done in finding an optimal solution. …”
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17
Loss reduction in distribution networks using new network reconfiguration algorithm
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18
Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…In this study a decision boundary equation, which is acquired from class conditional probability density function (PDF) of colors, based on Bayes decision theory has been used for desired color segmentation. The estimation of unknown PDF is a common problem and in this study Gaussian kernel function which is most widely used nonparametric density estimation method has been used for PDF calculation. …”
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19
Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems
Published 2023“…The best position and volume of DGs produce better power outcomes. This work prepares a new hybrid SSA–GWO metaheuristic optimization algorithm that combines the salp swarm algorithm (SSA) and the gray wolf optimizer (GWO) algorithm. …”
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Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems
Published 2023“…The best position and volume of DGs produce better power outcomes. This work prepares a new hybrid SSA–GWO metaheuristic optimization algorithm that combines the salp swarm algorithm (SSA) and the gray wolf optimizer (GWO) algorithm. …”
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