References in zbMATH (referenced in 894 articles )

Showing results 1 to 20 of 894.
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  1. De Mulder, Wim; Molenberghs, Geert; Verbeke, Geert: An interpretation of radial basis function networks as zero-mean Gaussian process emulators in cluster space (2020)
  2. Mauritzen, Johannes: Are solar panels commodities? A Bayesian hierarchical approach to detecting quality differences and asymmetric information (2020)
  3. Abboud, Candy; Bonnefon, Olivier; Parent, Eric; Soubeyrand, Samuel: Dating and localizing an invasion from post-introduction data and a coupled reaction-diffusion-absorption model (2019)
  4. Ahonen, Ilmari; Nevalainen, Jaakko; Larocque, Denis: Prediction with a flexible finite mixture-of-regressions (2019)
  5. Antonelli, Joseph; Parmigiani, Giovanni; Dominici, Francesca: High-dimensional confounding adjustment using continuous Spike and Slab priors (2019)
  6. Aswani, Anil; Kaminsky, Philip; Mintz, Yonatan; Flowers, Elena; Fukuoka, Yoshimi: Behavioral modeling in weight loss interventions (2019)
  7. Athey, Susan; Tibshirani, Julie; Wager, Stefan: Generalized random forests (2019)
  8. Azzimonti, Laura; Corani, Giorgio; Zaffalon, Marco: Hierarchical estimation of parameters in Bayesian networks (2019)
  9. Baker, Ruth E.; Parker, Andrew; Simpson, Matthew J.: A free boundary model of epithelial dynamics (2019)
  10. Bayliss, C. D.; Fallaize, C.; Howitt, R.; Tretyakov, M. V.: Mutation and selection in bacteria: modelling and calibration (2019)
  11. Bornn, Luke; Shephard, Neil; Solgi, Reza: Moment conditions and Bayesian non-parametrics (2019)
  12. Branson, Zach; Rischard, Maxime; Bornn, Luke; Miratrix, Luke W.: A nonparametric Bayesian methodology for regression discontinuity designs (2019)
  13. Browning, Alexander P.; Haridas, Parvathi; Simpson, Matthew J.: A Bayesian sequential learning framework to parameterise continuum models of melanoma invasion into human skin (2019)
  14. Bunji, Kyosuke; Okada, Kensuke: Item response and response time model for personality assessment via linear ballistic accumulation (2019)
  15. Chakraborty, Sounak; Lozano, Aurelie C.: A graph Laplacian prior for Bayesian variable selection and grouping (2019)
  16. Churchill, Victor; Gelb, Anne: Detecting edges from non-uniform Fourier data via sparse Bayesian learning (2019)
  17. Cockayne, Jon; Oates, Chris J.; Ipsen, Ilse C. F.; Girolami, Mark: A Bayesian conjugate gradient method (with discussion) (2019)
  18. Constantinou, Anthony C.: Dolores: a model that predicts football match outcomes from all over the world (2019)
  19. Costilla, Roy; Liu, Ivy; Arnold, Richard; Fernández, Daniel: Bayesian model-based clustering for longitudinal ordinal data (2019)
  20. da Paz, Rosineide F.; Balakrishnan, Narayanaswamy; Bazán, Jorge Luis: L-logistic regression models: prior sensitivity analysis, robustness to outliers and applications (2019)

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