Results 21 to 30 of about 327,047 (257)
Profile likelihood biclustering
Electronic Journal of Statistics, 2020 Biclustering, the process of simultaneously clustering the rows and columns of a data matrix, is a popular and effective tool for finding structure in a high-dimensional dataset. Many biclustering procedures appear to work well in practice, but most do not have associated consistency guarantees.
Flynn, Cheryl, Perry, Patrick
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Bayesian Inference in Extremes Using the Four-Parameter Kappa Distribution
Mathematics, 2020 Maximum likelihood estimation (MLE) of the four-parameter kappa distribution (K4D) is known to be occasionally unstable for small sample sizes and to be very sensitive to outliers.
Palakorn Seenoi +2 more
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Likelihood-based estimation and prediction for a measles outbreak in Samoa
Infectious Disease Modelling, 2023 Prediction of the progression of an infectious disease outbreak is important for planning and coordinating a response. Differential equations are often used to model an epidemic outbreak's behaviour but are challenging to parameterise. Furthermore, these
David Wu +4 more
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IEEE Access, 2020 A stochastic scheme, namely, PLM-Lap, has recently been propounded, which relies on the profile likelihood (PL) constructed with a Laplace distribution for estimating muscle activation onsets (MAOs) in surface electromyographic (sEMG) data.
Easter S. Suviseshamuthu +4 more
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Profile Maximum Likelihood Estimation of Single-Index Spatial Dynamic Panel Data Model
Mathematics, 2023 In this paper, the spatial dynamic panel data (SDPD) model is extended to the single-index spatial dynamic panel data (Si-SDPD) model by introducing a nonlinear connection function to reflect the interaction between explanatory variables.
Mengqi Zhang, Boping Tian
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Assessing parameter identifiability for Dynamic Causal Modelling of fMRI data
Frontiers in Neuroscience, 2015 Deterministic dynamic causal modelling (DCM) for fMRI data is a sophisticated approach to analyse effective connectivity in terms of directed interactions between brain regions of interest. To date it is difficult to know if acquired fMRI data will yield
Carolin eArand +6 more
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Multiplicative-Binomial Distribution: Some Results on Characterization, Inference and Random Data Generation [PDF]
Journal of Statistical Theory and Applications (JSTA), 2013 Multiplicative-binomial distribution is one of the distributions that allows for over-dispersion and under-dispersion relative to the standard binomial distribution.
Elsayed A.H. Elamir
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How to use χ2 test correctly——the likelihood ratio test and the implementation of SAS software
Sichuan jingshen weisheng, 2021 The purpose of this article was to introduce the likelihood ratio test and the SAS implementation. Specifically， three definitions of the likelihood ratio test statistics and six more commonly used likelihood ratio test statistics were introduced.
Hu Chunyan, Hu Liangping
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Approximate Profile Maximum Likelihood
J. Mach. Learn. Res., 2017 We propose an efficient algorithm for approximate computation of the profile maximum likelihood (PML), a variant of maximum likelihood maximizing the probability of observing a sufficient statistic rather than the empirical sample. The PML has appealing theoretical properties, but is difficult to compute exactly.
Dmitri S. Pavlichin +2 more
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Journal of Applied Mathematics, 2022 Numerical computation of maximum likelihood estimates (MLE) is one of the most common problems encountered in applied statistics. Even if there exist many algorithms considered as performing, they can suffer in some cases for one or many of the following
Issa Cherif Geraldo
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