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Bayesian estimation of a power law process with incomplete data

Hu Junming, Huang Hongzhong, Li Yanfeng
2021 Journal of Systems Engineering and Electronics  
To overcome this problem, from the point of view of order statistics, the statistical inference of the power law process with incomplete data is established in this paper.  ...  Order statistics offer an alternative to the statistical inference of the power law process with incomplete data as they can reformulate current studies on the left censored failure data and interval censored  ...  Acknowledgment The authors extend sincere gratitude to the Technology Institute of Armored Force for the data provided.  ... 
doi:10.23919/jsee.2021.000021 fatcat:xp55ueiapzd2xcus47oxhvviyy

Imputing continuous data under some non-Gaussian distributions

Hakan Demirtas, Donald Hedeker
2008 Statistica neerlandica (Print)  
with normal imputation models in terms of commonly accepted bias and precision measures, and discuss possible generalizations to the multivariate case and to larger families of distributions.  ...  Multiple imputation under such distributions that span a broader area in the symmetry-kurtosis plane appears to have the potential of better capturing real incomplete data trends.  ...  Acknowledgements We thank Dr Robin Mermelstein for access to the data; part of this work was supported by National Cancer Institute grant 5PO1 CA98262.  ... 
doi:10.1111/j.1467-9574.2007.00377.x fatcat:ymnw5ap7cveuplhk4pmvpj5jua

How players lose interest in playing a game: An empirical study based on distributions of total playing times

Christian Bauckhage, Kristian Kersting, Rafet Sifa, Christian Thurau, Anders Drachen, Alessandro Canossa
2012 2012 IEEE Conference on Computational Intelligence and Games (CIG)  
Therefore, given data on the initial playtime behavior of the players of a game, it becomes possible to predict when they stop playing. C. Bauckhage and K. Kersting are with Fraunhofer IAIS and the  ...  In all five cases, we find that the Weibull distribution gives a good account of the statistics of total playing times.  ...  The authors would like to direct special thanks to Jim Blackhurst and Tim Ward from Square Enix/Eidos team in London for their support, insights, and advice.  ... 
doi:10.1109/cig.2012.6374148 dblp:conf/cig/BauckhageKSTDC12 fatcat:gjd5zdyolbhkpdvhkkdturihoq

Water pipe condition assessment: a hierarchical beta process approach for sparse incident data

Zhidong Li, Bang Zhang, Yang Wang, Fang Chen, Ronnie Taib, Vicky Whiffin, Yi Wang
2013 Machine Learning  
Prediction of water pipe condition through statistical modelling is an important element for the risk management strategy of water distribution systems.  ...  The main aims of this work are three-fold: (1) For sparse incident data, develop an efficient approximate inference algorithm based on hierarchical beta process. (2) Apply the hierarchical beta process  ...  The authors extend their appreciation to Dammika Vitanage of Sydney Water Corporation for his expert commentaries.  ... 
doi:10.1007/s10994-013-5386-z fatcat:ziuqhnl7izdk7mj4bhft7f6b7a

Hierarchical statistical modeling of xylem vulnerability to cavitation

Kiona Ogle, Jarrett J. Barber, Cynthia Willson, Brenda Thompson
2009 New Phytologist  
We illustrate the method using data for roots and stems of two populations of Juniperus scopulorum and test for differences in k sat , P X , and S X between different groups. • Two important results emerge  ...  Weibull) can be reparameterized in terms of meaningful parameters: maximum conductivity (k sat ), water potential (-P) at which percentage loss of conductivity (PLC) = X% (P X ), and the slope of the PLC  ...  Jackson for logistical support and helpful discussion, and William T. Pockman for laboratory use and logistical support.  ... 
doi:10.1111/j.1469-8137.2008.02760.x pmid:19210723 fatcat:zwdzneeeuzdulpdcp3lrfyg5iy

On modelling positive continuous data with spatio-temporal dependence [article]

M.Bevilacqua, C. Caamaño, C. Gaetan
2020 arXiv   pre-print
For the proposed Weibull process we study the second-order and geometrical properties and we provide analytic expressions for the bivariate distribution.  ...  Moreover we tackle the prediction problem and we propose a linear prediction.  ...  W ( ESTIMATION AND PREDICTION Pairwise likelihood inference Suppose that we have observed y 1 , . . . , y n at the locations s 1 , . . . , s n and let θ be the vector of unknown parameters for the  ... 
arXiv:1808.03829v4 fatcat:grm2skdmzfgwdbuvwjphxj3znq

Age-Dependent Speciation Can Explain the Shape of Empirical Phylogenies

Oskar Hagen, Klaas Hartmann, Mike Steel, Tanja Stadler
2015 Systematic Biology  
From such trees, inferences can be made about the underlying macroevolutionary processes, yet remarkably these processes are still poorly understood.  ...  The biological motivation for the identified age-dependent speciation process may be that recently evolved taxa often colonize new regions or niches and may initially experience little competition.  ...  ACKNOWLEDGMENTS The authors thank the editors Frank Anderson, Laura Kubatko, and four anonymous reviewers for their extensive and constructive suggestions.  ... 
doi:10.1093/sysbio/syv001 pmid:25575504 pmcid:PMC4395845 fatcat:qxjfwqixabfvhls3bl24njnave

NONLINEAR ESTIMATION OF GROWTH CURVE MODELS FOR GERMINATION DATA ANALYSIS

Bahman Shafii, William J. Price, Jerry B. Swensen, Glen A. Murray
1991 Conference on Applied Statistics in Agriculture  
The nonlinear estimation of the germination response included a parameter summary, together with their asymptotic standard errors and correlation matrix, along with an approximate band for the expectation  ...  function, pairwise plots of the parameter inference region, and profile t plots.  ...  and they are, for the most part, ambiguous and incomplete.  ... 
doi:10.4148/2475-7772.1415 fatcat:uwc6f67xvbh75jsdku7mprha5a

Warranty forecasting of electronic boards using short-term field data

Vehbi Comert, Mustafa Altun, Mustafa Nadar, Ertunc Erturk
2015 2015 Annual Reliability and Maintainability Symposium (RAMS)  
Before using the field data for our model of warranty forecasting, we filter it to eliminate improper data, correlated to incomplete and poorly collected data.  ...  In the fitting process we use and compare "Bayesian", "rank regression", and "maximum likelihood" fitting techniques. Our method has two steps.  ...  For this study statistical inferences are based on Weibull distribution and its beta (β) parameter. Weibull β parameter can take values in three region; 0< β < 1, β = 1, β > 1.  ... 
doi:10.1109/rams.2015.7105104 fatcat:m5lei2xcuvf27lhyfsejsiquxm

Estimating Age-Dependent Extinction: Contrasting Evidence from Fossils and Phylogenies

Oskar Hagen, Tobias Andermann, Tiago B Quental, Alexandre Antonelli, Daniele Silvestro, Michael Alfaro
2017 Systematic Biology  
This assumption of age-independent extinction has prevailed for decades with its assessment based on survivorship curves, which, however, do not directly account for the incompleteness of the fossil record  ...  Our approach, unlike previous implementations, explicitly models unobserved species and accounts for the effects of fossil preservation on the observed longevity of sampled lineages.  ...  We also thank the editors, Michael Alfaro and Thomas Near, Thomas Ezard, and one anonymous reviewer for valuable comments on this manuscript.  ... 
doi:10.1093/sysbio/syx082 pmid:29069434 pmcid:PMC5920349 fatcat:bad2pkjpd5dqnkdkafli2fzlhu

Bayesian Weibull tree models for survival analysis of clinico-genomic data

Jennifer Clarke, Mike West
2008 Statistical Methodology  
However, the need exists for models which examine how genomic predictors interact with existing clinical factors and provide personalized outcome predictions.  ...  We have developed clinico-genomic tree models for survival outcomes which use recursive partitioning to subdivide the current data set into homogeneous subgroups of patients, each with a specific Weibull  ...  Inference and prediction Inference and prediction at a terminal node or leaf of a given tree involve the calculation of branch probabilities and the posterior predictive distributions which underlie the  ... 
doi:10.1016/j.stamet.2007.09.003 pmid:18618012 pmcid:PMC2447923 fatcat:kawd25n5hvctje5pmx6qdkro5m

On Mechanistic Modeling of Gene Content Evolution: Birth-Death Models and Mechanisms of Gene Birth and Gene Retention

Ashley Teufel, Jing Zhao, Malgorzata O'Reilly, Liang Liu, David Liberles
2014 Computation  
The interplay between complex biological processes and necessarily simpler statistical models leads to a complex modeling problem.  ...  A discussion of the relationship between biological processes, existing models for duplicate gene retention and data is presented.  ...  Acknowledgments We thank Michael Woodhams, Tanja Stadler, Cathal Seoighe, Laura Kubatko, Anne Sylvester, Jan Kubelka and Tristan Stark for helpful discussions.  ... 
doi:10.3390/computation2030112 fatcat:xv6zxmrmuzc63e4tfxai2jlpfa

Page 4436 of Mathematical Reviews Vol. , Issue 87h [page]

1987 Mathematical Reviews  
Statist. 9 (1981), no. 2, 356-367; MR 82d:62148] and shows that if the failure rate function is taken to be the sum of a nonnegative stochastic process with increasing sample paths and a process with decreasing  ...  The asymptotic relative efficiency of this statistic is obtained and its numerical values are computed for uniform and Weibull censor- ing.  ... 

Cure Models based on Weibull Distribution with and without Covariates using Right Censored Data

Madaki Umar Yusuf, Mohd Rizam B. Abu Bakar
2016 Indian Journal of Science and Technology  
a great indication of similarity with the covariates and flexibility of the models.  ...  Inferences for the models are obtained under the Bayesian approach via Markov Chain Monte Carlo (MCMC) where the posterior estimates were obtained by using Metropolis-Hastings sampling methods in the presence  ...  The LPML is derived from the Conditional Predictive Ordinate (CPO) statistics 13 .  ... 
doi:10.17485/ijst/2016/v9i28/97350 fatcat:njsbzpggbvfplbjlmc24kabque

Comparison Of Regression Imputation Methods Of Baseline Covariates that Predict Survival Outcomes

Nicole Solomon, Yuliya Lokhnygina, Susan Halabi
2020 Journal of Clinical and Translational Science  
Missing data are inevitable in medical research and appropriate handling of missing data is critical for statistical estimation and making inferences.  ...  LASSO and SVM outperform GLM, MARS, and RF in the context of regression imputation for prediction of a time-to-event outcome.  ...  Acknowledgements The authors thank Sanofi for sharing their data and making this analysis possible. Dr. Barry Moser contributed to the design and analysis plan of this study.  ... 
doi:10.1017/cts.2020.533 pmid:33948262 pmcid:PMC8057424 fatcat:knxikuiv7ragpnrpi7tyyv2ama
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