Working with Car Parking Data for Bath and North East Somerset
c(person("Owen", "Jones", email = "olj23@bath.ac.uk", role = c("aut", "cre")),
person("Ryan", "Kenning", role = c("aut", "ctb")))
Contains functions for importing and working with the BANES car parking
records and other related datasets. For the full version of the package, including
all datasets, see the repo at <https://github.com/owenjonesuob/BANEScarparking>.
The original dataset of parking records can be found at
<https://data.bathhacked.org/Government-and-Society/BANES-Historic-Car-Park-Occupancy/x29s-cczc>.
dplyr, httr, lubridate, RCurl, readr, rvest, utils, XML, xml2,
zoo
Owen Jones [aut, cre],
Ryan Kenning [aut, ctb]

c(person("Owen", "Jones", email = "joneso21164@gmail.com", role = c("aut", "cre")),
person("Ryan", "Kenning", role = c("aut", "ctb")),
person("Nick", "Howlett", role = "ctb"))
dplyr, httr, lubridate, RCurl, readr, rvest, utils, XML, xml2
Owen Jones [aut, cre],
Ryan Kenning [aut, ctb],
Nick Howlett [ctb]

Provides efficient Bayesian nonparametric models for network feature selection
DPpackage, igraph, mclust, pscl, tmvtnorm, network
Zhou Lan, Yize Zhao, Jian Kang, Tianwei Yu

Provides a full package of posterior inference, model comparison, and graphical illustration of model fitting. A parallel computing algorithm for the Markov chain Monte Carlo (MCMC) based posterior inference and an Expectation-Maximization (EM) based algorithm for posterior approximation are are developed, both of which greatly reduce the computational time for model inference.

DPpackage, igraph, mclust, pscl, tmvtnorm, network, coda

DPpackage, igraph, mclust, pscl, tmvtnorm, network, coda,
graphics, methods, stats, utils

DPpackage, igraph, mclust, network, GGally, truncnorm,
graphics, stats, flexmix, grDevices,foreach, doParallel, coda,
pscl,methods,
Zhuxuan Jin, Zhou Lan, Yize Zhao, Jian Kang, Tianwei Yu

BANOVA: Hierarchical Bayesian ANOVA Models
jags (>= 3.3.0, see
http://mcmc-jags.sourceforge.net)
BANOVA covers several Bayesian Analysis of Variance (BANOVA) models used in analysis of experimental designs in which both within- and between- subjects factors are manipulated. They can be applied to data that are common in the behavioral sciences and related fields. The package includes: Hierarchical Bayes ANOVA models with normal response, t response, Binomial(Bernoulli) response, Poisson response, ordered multinomial response and multinomial response variables. All models accommodate unobserved heterogeneity by including a normal distribution of the parameters across individuals. Outputs of the package include tables of sums of squares, effect sizes and p-values, and tables of means, which are easily interpretable for behavioral researchers. BANOVA uses JAGS as the computational platform.