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Performance in population models for count data, part II: a new SAEM algorithm.
... Results: Overall, the estimation procedure with the SAEM algorithm in a non-linear mixed effect modelling framework for count data models, showed satisfactory performance with low bias and high precision. ...
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Prediction of subplastidial localization of chloroplast proteins from spectral count data - Comparison of machine learning algorithms
... spectral count data - Comparison of machine learning algorithms Thomas Burger (1) , Samuel Wieczorek (1) , Christophe Masselon (1) , Daniel Salvi (2) , Norbert Rolland (2) , Myriam Ferro (1) ...
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Time Series of Correlated Count Data using Multifractal Process
... of count. Based on real data, the correlated multifractal model is used to model the number of claims of two separate coverages in automobile ...between count variables, we think that it can be ...
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Bayesian estimation of bandwidth in semiparametric kernel estimation of unknown probability mass and regression functions of count data
... are count data, generalized linear models (GLM) studied by McCullagh and Nelder (1989) for these cases can serve as parametric start regres- sion models r( ·; ...
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Parametric Modelling of Multivariate Count Data Using Probabilistic Graphical Models
... Multivariate count data are defined as the number of items of different categories issued from sampling within a population, which individuals are grouped into ...multivariate count data is a ...
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Spatial spillovers in France: a study on individual count data at the city level
... patent data as dependent variable. These are count data, characterised by non-negative integer numbers and an important number of ...aggregated data, we concentrate on individual ...
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Nonparametric estimation of renewal processes from count data.
... the count data (and consequently smaller dispersions of the es- timated inter-event ...real data (Figures 11 and 12) with the results of the small sample simulation ...
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tabula: An R Package for Analysis, Seriation, and Visualization of Archaeological Count Data
... these classes provide tools for relative and absolute dating and analysis of (chronological) patterns. tabula includes functions for matrix seriation (seriate_*), as well as chronological model- ing and dating (date_*) ...
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Poisson noise removal in multivariate count data
... 5. CONCLUSION In this paper, we propose a multivalued extension of MSVST associated with an appropriate 2D-1D wavelet transform, which proved very efficient to denoise Poisson count data. The proposed ...
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Fitting the truncated negative binomial distribution to count data. A comparison of estimators, with an application to groundfishes from the Mauritanian Exclusive Economic Zone
... CLAUDE MANTÉ, SAÏKOU OUMAR KIDÉ, A.F. YAO, BASTIEN MÉRIGOT Abstract. A frequent issue in the study of species abundance consists in modeling empirical distributions of repeated counts by parametric probability ...
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Innovation and training: a dynamic count data model
... In count data models, where a non-linearity is produced by the non-negative discrete nature of the data, the standard generalized method of moments (GMM) for the estimation of xed eects models is ...
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On the use of ATSR fire count data to estimate the seasonal and interannual variability of vegetation fire emissions
... variability for North American fires compares well even in relative magnitude, whereas the CO emissions show less variability than the burned area estimates in Russia. It is possible that this di fference can be ...
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Time Series of Count Data using Multifractal Process
... polio data, a classic data set for time series of counts, rst used by Zeger (1988), and later by Chan & Ledolter (1995), Kuk & Cheng (1997), Oh & Lin (2001), Jung & Liesenfeld (2001), and ...
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DiscreteTS : two hidden-Markov models for time series of count data
... zeros. Pro
eedings of ESANN 2012, 133-138 [4℄ Ridgway J. (2011). Hidden Markov models for time series of ount data. Rapport de stage [5℄ Hamilton J.D. (1989). A new approa
h to the e
onomi analysis of ...
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Discrete-time risk models based on time series for count random variables.
... Other models such as models based on copulas, where the marginals are …xed and the depen- dence structure is based on a copula (see e.g. Joe (1997) and Frees and Wang (2006)), could have been considered. A review on time ...
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The Dynamic Latent Block Model for Sparse and Evolving Count Matrices
... missing data that may evolve along the time. For instance, such data are commonly produced by e-commerce systems which record in continuous time all purchases of products made by cus- ...the count ...
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Multi-scale variance stabilizing transform for multi-dimensional Poisson count image denoising
... Institut Pasteur 75724 Paris France 14050 Caen France 91191 Gif-sur-Yvette France ABSTRACT We propose in this paper a Multi-Scale Variance Stabilizing Transform (MSVST) for approximately Gaussianizing and sta- bilizing ...
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Core Count vs Cache Size for Manycore Architectures in the Cloud
... Second, it is surprising to see that the optimal configuration in 90nm with an SRAM L2 contains no L2 cache, but has 16KB L1I and 32KB L1D caches. This is largely due to the fact that decent sized caches can be built at ...
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Improving Gross Count Gamma-Ray Logging in Uranium Mining With the NGRS Probe
... simulated data, evidencing linear correlations between the correction and different parameters including information on the borehole diameter, density of filli g f uids, tube material, and thick- ...
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Efficiency and effectiveness evaluation of an automated multi-country patient count cohort system
... Iñaki Soto-Rey 1* , Benjamin Trinczek 1 , Yannick Girardeau 2,3 , Eric Zapletal 2 , Nadir Ammour 4 , Justin Doods 1 , Martin Dugas 1 and Fleur Fritz 1 Abstract Background: With the increase of clinical trial costs during ...
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