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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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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…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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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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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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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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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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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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Detection of multiple outliners in linear regression using nonparametric methods
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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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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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Data discovery algorithm for scientific data grid environment
Published 2005“…By using this model, we study various discovery algorithms for locating data sets in a data grid system. …”
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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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15
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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Binary Vote Assignment on Cloud Quorum Algorithm for Fragmented MyGRANTS Database Replication
Published 2015“…This paper proposed a new algorithm namely Binary Vote Assignment on Cloud Quorum (BVACQ) in order to handle fragmented database replication in distributed environment. …”
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Ancestral dynamic voting algorithm for mutual exclusion in partitioned distributed systems
Published 2013“…Data replication is a known redundancy used in fault-tolerant distributed system. …”
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Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification
Published 2018“…It still takes a long time to compute the topic distribution of the data. …”
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Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification
Published 2018“…It still takes a long time to compute the topic distribution of the data. …”
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A novel binary vote assignment grid quorum algorithm for distributed database fragmentation
Published 2011“…This paper propose a new algorithm namely Binary Vote Assignment on Grid Quorum (BVAGQ) in order to handle data replication and transaction management. …”
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