Zobrazeno 1 - 10
of 148
pro vyhledávání: '"Matt P. Wand"'
Publikováno v:
Journal of Statistical Software, Vol 87, Iss 1, Pp 1-37 (2018)
We provide several examples of Bayesian semiparametric regression analysis via the Infer.NET package for approximate deterministic inference in Bayesian models. The examples are chosen to encompass a wide range of semiparametric regression situations
Externí odkaz:
https://doaj.org/article/819f689146724410826064e4d34f6f4c
Autor:
Matt P. Wand, J. C. F. Yu
Publikováno v:
AStA Advances in Statistical Analysis. 106:199-216
We explain how effective automatic probability density function estimates can be constructed using contemporary Bayesian inference engines such as those based on no-U-turn sampling and expectation propagation. Extensive simulation studies demonstrate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff11ffac3324868c544792d89f2b0848
https://doi.org/10.1007/s10182-021-00422-8
https://doi.org/10.1007/s10182-021-00422-8
Autor:
Luca Maestrini, Matt P. Wand
Publikováno v:
Australian & New Zealand Journal of Statistics. 63:517-541
Message passing on a factor graph is a powerful paradigm for the coding of approximate inference algorithms for arbitrarily graphical large models. The notion of a factor graph fragment allows for compartmentalization of algebra and computer code. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14749480a1cd254324ee81c9c9bbe0d1
https://doi.org/10.1111/anzs.12339
https://doi.org/10.1111/anzs.12339
Publikováno v:
BIOSTATISTICS
Summary Collecting information on multiple longitudinal outcomes is increasingly common in many clinical settings. In many cases, it is desirable to model these outcomes jointly. However, in large data sets, with many outcomes, computational burden o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39c3fdc5ecb804edd7a8fc9b17c3a219
https://doi.org/10.1093/biostatistics/kxab021
https://doi.org/10.1093/biostatistics/kxab021
Publikováno v:
Stat Modelling
A two-level group-specific curve model is such that the mean response of each member of a group is a separate smooth function of a predictor of interest. The three-level extension is such that one grouping variable is nested within another one, and h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe401fe41b45c55c8dd016831bebb370
https://doi.org/10.1177/1471082x20930894
https://doi.org/10.1177/1471082x20930894
We derive precise asymptotic results that are directly usable for confidence intervals and Wald hypothesis tests for likelihood-based generalized linear mixed model analysis. The essence of our approach is to derive the exact leading term behaviour o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::057272b7beb05eed9b70075d282f3671
https://hdl.handle.net/10453/151814
https://hdl.handle.net/10453/151814
Linear mixed models are a versatile statistical tool to study data by accounting for fixed effects and random effects from multiple sources of variability. In many situations, a large number of candidate fixed effects is available and it is of intere
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::044bf915e85b9700db6258959bfc05a0
Autor:
Tui H. Nolan, Matt P. Wand
We define and solve classes of sparse matrix problems that arise in multilevel modelling and data analysis. The classes are indexed by the number of nested units, with two-level problems corresponding to the common situation, in which data on level-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91d5a99951389af67fddaed42ac9820f
https://hdl.handle.net/10453/146961
https://hdl.handle.net/10453/146961
Autor:
Matt P. Wand, Tung Pham
Publikováno v:
Australian & New Zealand Journal of Statistics. 60:279-300
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::691adf936c2a4eeffbf2e83923133b2c
https://doi.org/10.1111/anzs.12241
https://doi.org/10.1111/anzs.12241
Publikováno v:
Forensic Chemistry. 9:62-75
© 2018 Elsevier B.V. Blood-detection dogs are trained to locate blood evidence and search for potential crime scenes in cases where a cadaver may not be present. The locations of crime scenes are often ambiguous and evidence may not always be obviou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51a5957015e415aff98398f02bf2afae
https://doi.org/10.1016/j.forc.2018.05.002
https://doi.org/10.1016/j.forc.2018.05.002