Packaged: 2015-08-10 22:00:45 UTC; matthewjdenny

Exponential Random Graph Models (GERGM) via Gibbs sampling or Metropolis
Imports: Rcpp, ggplot2, methods, stringr, igraph
Packaged: 2015-11-13 15:25:48 UTC; matthewjdenny

Packaged: 2015-11-17 04:16:14 UTC; matthewjdenny

Imports: Rcpp, ggplot2, methods, stringr, igraph, plyr
Packaged: 2015-12-04 04:22:29 UTC; matthewjdenny

Packaged: 2015-12-19 21:09:50 UTC; matthewjdenny

Imports: Rcpp, ggplot2, methods, stringr, igraph, plyr, parallel, coda
Packaged: 2016-01-18 20:00:00 UTC; matthewjdenny

Description: Implements the gene-based segregation test(GESE) and the weighted GESE test for identifying genes with causal variants of large effects for family-based sequencing data. The methods are described in Qiao, D. Lange, C., Laird, N.M., Won, S., Hobbs, B., et al. 2016. Gene-based segregation method for identifying rare variants for family-based sequencing studies. More details can be found at <http://scholar.harvard.edu/dqiao/gese>.

Description: Implements the gene-based segregation test(GESE) and the weighted GESE test for identifying genes with causal variants of large effects for family-based sequencing data. The methods are described in Qiao, D. Lange, C., Laird, N.M., Won, S., Hersh, C.P., et al. (2017). <DOI:10.1002/gepi.22037>. Gene-based segregation method for identifying rare variants for family-based sequencing studies. Genet Epidemiol 41(4):309-319. More details can be found at <http://scholar.harvard.edu/dqiao/gese>.

Title: Gene Expression State Transformation
Description: The Gene Expression State Transformation (GESTr) models
the states of expression of genes across a compendium of
samples in order to provide a universal scale of gene
expression for all genes. TranSAM is a modification of the SAM
approach designed to utilise GESTr-transformed gene expression

person(given = 'Mari', family = 'Myllymäki', role = c('aut', 'cre'),
person(given = 'Tomáš', family = 'Mrkvička', role = 'aut',
person(given = 'Pavel', family = 'Grabarnik', role = 'ctb',
person(given = 'Ute', family = 'Hahn', role = 'ctb',
person(given = 'Mikko', family = 'Kuronen', role = 'ctb',
person(given = 'Michael', family = 'Rost', role = 'ctb',
person(given = 'Henri', family = 'Seijo', role = 'ctb',
Imports: caTools, fda.usc, ggplot2, graphics, grDevices, gridExtra,
gstat, methods, parallel, plyr, sp, spatstat, stats, utils,
Description: Implementation of global envelopes with intrinsic graphical interpretation which can be used for graphical Monte Carlo and permutation tests where the test statistic is a multivariate vector or function (e.g. goodness-of-fit testing for point patterns and random sets, functional analysis of variance, functional general linear model, n-sample test of correspondence of distribution functions), for central regions of functional or multivariate data (e.g. outlier detection, functional boxplot) and for global confidence and prediction bands (e.g. confidence band in polynomial regression, Bayesian posterior prediction). See Myllymäki et al. (2017) <doi: 10.1111/rssb.12172>, Mrkvička et al. (2017) <doi: 10.1007/s11222-016-9683-9>, Mrkvička et al. (2016) <doi: 10.1016/j.spasta.2016.04.005>, Mrkvička et al. (2018) <arXiv:1612.03608>, Mrkvička et al. (2019) <arXiv:1906.09004>, Mrkvička et al. (2019) <arXiv:1902.04926>.