Suchergebnisse - "Computational methods for problems pertaining to statistics"

An Approximate Control Variates Approach to Multifidelity Distribution Estimation: An approximate control variates approach to multifidelity distribution estimation

Autoren: Ruijian Han Boris Kramer Dongjin Lee et al.

Quelle: SIAM/ASA Journal on Uncertainty Quantification. 12:1349-1388

Schlagwörter: FOS: Computer and information sciences, model selection, Linear regression, mixed models, Nonparametric robustness, Monte Carlo methods, robustness, Numerical Analysis (math.NA), Statistics - Computation, Statistics - Applications, 01 natural sciences, control variates, multifidelity, Asymptotic properties of nonparametric inference, distribution estimation, FOS: Mathematics, Applications (stat.AP), Mathematics - Numerical Analysis, 0101 mathematics, Computational methods for problems pertaining to statistics, Nonparametric estimation, Computation (stat.CO)

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/abs/2303.06422

Projection predictive variable selection for discrete response families with finite support

Autoren: Frank Weber Änne Glass Aki Vehtari

Quelle: Computational Statistics. 40:701-721

Schlagwörter: FOS: Computer and information sciences, post-selection inference, 05 social sciences, ordinal, nominal, 02 engineering and technology, Bayesian, 01 natural sciences, Methodology (stat.ME), 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, 62F15 (Primary) 62F07, 62J99 (Secondary), 0101 mathematics, Computational methods for problems pertaining to statistics, Statistics - Methodology, variable selection

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/abs/2301.01660

Robust Bayesian cumulative probit linear mixed models for longitudinal ordinal data

Autoren: Kuo-Jung Lee Ray-Bing Chen Keunbaik Lee

Quelle: Computational Statistics. 40:441-468

Schlagwörter: hypersphere decomposition, MCMC, correlation matrix, random effects, Computational methods for problems pertaining to statistics

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/8014970
https://doi.org/10.1007/s00180-024-01499-w

Debiased transfer learning estimation and inference for multinomial regression

Autoren: Yang, Jichen Wang, Lei Lian, Heng

Quelle: Statistics and Computing. 35

Schlagwörter: source detection, Parametric tolerance and confidence regions, Ridge regression, shrinkage estimators (Lasso), Classification and discrimination, cluster analysis (statistical aspects), asymptotic normality, debiased Lasso, nodewise quadratic programming, Computational methods for problems pertaining to statistics, confidence intervals

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/8029197
https://doi.org/10.1007/s11222-025-10607-9

Bayesian analysis of doubly semiparametric mixture cure models with interval-censored data

Autoren: Liu, Xiaoyu Xiang, Liming

Quelle: Statistics and Computing. 35

Schlagwörter: Censored data models, interval censoring, Bayesian inference, augmentation, Bayesian analysis, Estimation in survival analysis and censored data, splines, Computational methods for problems pertaining to statistics, mixture cure model, Applications of statistics to biology and medical sciences, meta analysis

Dateibeschreibung: application/xml

Metropolis-adjusted interacting particle sampling

Autoren: Sprungk, Björn Weissmann, Simon Zech, Jakob

Quelle: Statistics and Computing. 35

Schlagwörter: interacting particle systems, Bayesian inference, Monte Carlo methods, Mathematics - Numerical Analysis, Computational methods for problems pertaining to statistics, Metropolis-Hastings, Statistics - Computation

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/abs/2312.13889
https://zbmath.org/8029188
https://doi.org/10.1007/s11222-025-10595-w

Hyperparameter optimization for randomized algorithms: a case study on random features

Autoren: Dunbar, Oliver R. A. Nelsen, Nicholas H. Mutic, Maya

Quelle: Statistics and Computing. 35

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, hyperparameter learning, Bayesian inference, Bayesian inverse problems, Machine Learning (stat.ML), Statistics - Computation, ensemble Kalman inversion, Machine Learning (cs.LG), Statistics - Machine Learning, random features, Computational methods for problems pertaining to statistics, Gaussian process regression, Computation (stat.CO)

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/abs/2407.00584
https://zbmath.org/8005884
https://doi.org/10.1007/s11222-025-10587-w

Anisotropic multidimensional smoothing using Bayesian tensor product P-splines

Autoren: Bach, Paul Klein, Nadja

Quelle: Statistics and Computing, 35 (2), Art.-Nr.: 43

Schlagwörter: ddc:004, FOS: Computer and information sciences, Generalized linear models (logistic models), Kronecker sum, penalized splines, DATA processing & computer science, 05 social sciences, functional ANOVA decomposition, multivariate smoothing, Statistics - Computation, 01 natural sciences, Methodology (stat.ME), Functional data analysis, Markov chain Monte Carlo, 0502 economics and business, Nonparametric regression and quantile regression, 0101 mathematics, Computational methods for problems pertaining to statistics, Statistics - Methodology, Computation (stat.CO), spatio-temporal statistics

Dateibeschreibung: application/xml; application/pdf

Zugangs-URL: http://arxiv.org/abs/2211.16218
https://zbmath.org/8005871
https://doi.org/10.1007/s11222-025-10569-y

Robust and efficient sparse learning over networks: a decentralized surrogate composite quantile regression approach

Autoren: Qiao, Nan Chen, Canyi Zhu, Zhengtian

Quelle: Statistics and Computing. 35

Schlagwörter: Ridge regression, shrinkage estimators (Lasso), Estimation in multivariate analysis, decentralized estimation, composite quantile regression, heavy-tailed noise, Nonparametric regression and quantile regression, heterogeneity, Computational methods for problems pertaining to statistics, support recovery

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7983932
https://doi.org/10.1007/s11222-024-10547-w

Likelihood inference for unified transformation cure model with interval censored data

Autoren: Jodi Treszoks Suvra Pal

Quelle: Computational Statistics. 40:125-151

Schlagwörter: interval censoring, proportional hazards, Computational methods for problems pertaining to statistics, EM algorithm, profile likelihood, smoking cessation

Dateibeschreibung: application/xml

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40012557

Simultaneous confidence bands for multiple comparisons of several percentile lines

Autoren: Sanyu Zhou Yu Zhang

Quelle: Computational Statistics. 40:111-123

Schlagwörter: regression, simultaneous inference, Computational methods for problems pertaining to statistics, simulation

Dateibeschreibung: application/xml

Variational Bayesian Lasso for spline regression

Autoren: Larissa C. Alves Ronaldo Dias Helio S. Migon

Quelle: Computational Statistics. 39:2039-2064

Schlagwörter: Computational methods for problems pertaining to statistics, evidence lower bound, knots selection, mean field posterior approximation, variational inference

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7904612
https://doi.org/10.1007/s00180-024-01470-9

Differentiated uniformization: a new method for inferring Markov chains on combinatorial state spaces including stochastic epidemic models

Autoren: Rupp, Kevin Schill, Rudolf Süskind, Jonas et al.

Quelle: 13 Seiten (2021). doi:10.48550/ARXIV.2112.10971

Schlagwörter: FOS: Computer and information sciences, ddc:610, Computer Science - Machine Learning, ddc:530, Bayesian inference, 610 Medizin, Populations and Evolution (q-bio.PE), Machine Learning (stat.ML), 530 Physik, uniformization, Continuous-time Markov chains · Bayesian inference · Uniformization · Matrix exponential · Tensors · Epidemic spread, 01 natural sciences, continuous-time Markov chains, matrix exponential, 3. Good health, Machine Learning (cs.LG), tensors, Statistics - Machine Learning, FOS: Biological sciences, epidemic spread, 0101 mathematics, Computational methods for problems pertaining to statistics, Quantitative Biology - Populations and Evolution

Dateibeschreibung: application/xml; application/pdf

Zugangs-URL: http://arxiv.org/abs/2112.10971
https://zbmath.org/8014318
https://doi.org/10.1007/s00180-024-01454-9
https://publications.rwth-aachen.de/record/842166
https://epub.uni-regensburg.de/55492/

Simultaneous subgroup identification and variable selection for high dimensional data

Autoren: Huicong Yu Jiaqi Wu Weiping Zhang

Quelle: Computational Statistics. 39:3181-3205

Schlagwörter: subgroups, sparsity, heterogeneity, Computational methods for problems pertaining to statistics, ADMM, oracle property

Dateibeschreibung: application/xml

On the Representation and Learning of Monotone Triangular Transport Maps: On the representation and learning of monotone triangular transport maps

Autoren: Baptista, Ricardo Marzouk, Youssef Zahm, Olivier et al.

Weitere Verfasser: Baptista, Ricardo Marzouk, Youssef Zahm, Olivier et al.

Quelle: Foundations of Computational Mathematics. 24:2063-2108

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Optimal transportation, Monotone functions, infinite-dimensional optimization, Machine Learning (stat.ML), 02 engineering and technology, Wavelets, wavelets, Statistics - Computation, 01 natural sciences, Machine Learning (cs.LG), Methodology (stat.ME), Approximation by polynomials, normalizing flows, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, Knothe-Rosenblatt rearrangement, density estimation, adaptive approximation, 62G07, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 0101 mathematics, multivariate polynomials, Statistics - Methodology, Computation (stat.CO), Knothe–Rosenblatt rearrangement, Infinite-dimensional optimization, monotone functions, 49Q22, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], Functional Analysis (math.FA), Multivariate polynomials, Mathematics - Functional Analysis, Density estimation, Transportation of measure, 65C20, Computational methods for problems pertaining to statistics, Normalizing flows, Adaptive approximation

Dateibeschreibung: application/xml; application/pdf

Zugangs-URL: http://arxiv.org/abs/2009.10303
https://zbmath.org/7963971
https://doi.org/10.1007/s10208-023-09630-x

Random perturbation subsampling for rank regression with massive data

Autoren: He, Sijin Xia, Xiaochao

Quelle: Statistics and Computing. 35

Schlagwörter: massive data, Statistical aspects of big data and data science, consistency, random perturbation subsampling, rank regression, asymptotic normality, Nonparametric regression and quantile regression, Computational methods for problems pertaining to statistics

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7983922
https://doi.org/10.1007/s11222-024-10548-9

Gaussian measures conditioned on nonlinear observations: consistency, MAP estimators, and simulation

Autoren: Chen, Yifan Hosseini, Bamdad Owhadi, Houman et al.

Quelle: Statistics and Computing. 35

Schlagwörter: FOS: Computer and information sciences, Inverse problems for PDEs, Computer Science - Machine Learning, Bayesian inference, Probability (math.PR), Learning and adaptive systems in artificial intelligence, Machine Learning (stat.ML), Numerical Analysis (math.NA), Statistics - Computation, Gaussian measures, Machine Learning (cs.LG), Statistics - Machine Learning, FOS: Mathematics, conditional probability, Mathematics - Numerical Analysis, Computational methods for problems pertaining to statistics, Mathematics - Probability, Computation (stat.CO)

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/abs/2405.13149
https://zbmath.org/7983918
https://doi.org/10.1007/s11222-024-10535-0

A Review of Generalized Linear Latent Variable Models and Related Computational Approaches: A review of generalized linear latent variable models and related computational approaches

Autoren: Pekka Korhonen Klaus Nordhausen Sara Taskinen

Quelle: WIREs Computational Statistics. 16

Schlagwörter: todennäköisyyslaskenta, MCMC, Statistics, 05 social sciences, School of Resource Wisdom, factor analysis, Gauss-Hermite, quasi-likelihood, Gauss–Hermite, 01 natural sciences, Resurssiviisausyhteisö, faktorianalyysi, 0504 sociology, likelihood function, 0101 mathematics, Computational methods for problems pertaining to statistics, Laplace approximation, Tilastotiede

Dateibeschreibung: application/xml; application/pdf; fulltext

Zugangs-URL: http://urn.fi/URN:NBN:fi:jyu-202411157305

Online prediction of extreme conditional quantiles via B-spline interpolation

Autoren: Li, Zhengpin Wang, Jian Hou, Yanxi

Quelle: Statistics and Computing. 34

Schlagwörter: Methodology (stat.ME), FOS: Computer and information sciences, extreme conditional quantile, quantile regression, Statistics of extreme values, tail inference, B-splines, generalized Pareto distribution, Nonparametric regression and quantile regression, Computational methods for problems pertaining to statistics, Statistics - Computation, Statistics - Methodology, Computation (stat.CO)

Dateibeschreibung: application/xml

Zugangs-URL: http://arxiv.org/abs/2311.13825

K-fold cross-validation based frequentist model averaging for linear models with nonignorable missing responses: \(K\)-fold cross-validation based frequentist model averaging for linear models with nonignorable missing responses

Autoren: Liang, Zhongqi Cai, Li Wang, Suojin et al.

Quelle: Statistics and Computing. 35

Schlagwörter: Linear regression, mixed models, asymptotic optimality, selection consistency, nonignorable missing, model averaging, Nonparametric regression and quantile regression, Computational methods for problems pertaining to statistics, cross-validation

Dateibeschreibung: application/xml

Zugangs-URL: https://zbmath.org/7983926
https://doi.org/10.1007/s11222-024-10554-x