tidyselect, janitor, Rcpp, rlang, ggrepel, diagonals

Title: Hierarchical latent space network model (HLSM)
Author: Samrachana Adhikari, Brian Junker, Tracy Sweet, Andrew C. Thomas
Description: Hierarchical latent space network model for ensemble of networks

Title: Hierarchical Latent Space Network Model (HLSM)
Description: Hierarchical latent space network model for fitting ensemble of networks.
Imports: MASS, coda, grDevices, graphics, stats

Description: R-package to implement Hierarchical Latent Space Network Model (HLSM) for ensemble of networks as described in Sweet et. al. (2012).<DOI:10.3102/1076998612458702>.
Packaged: 2016-10-19 12:38:09 UTC; samrachanaadhikari

Title: Hierarchical Latent Space Network Model
Description: Implements Hierarchical Latent Space Network Model (HLSM) for ensemble of networks as described in Sweet et. al. (2012). <DOI:10.3102/1076998612458702>.
Packaged: 2016-11-25 02:25:49 UTC; samrachanaadhikari

Packaged: 2019-04-30 13:52:12 UTC; adityabhat

Description: Implements Hierarchical Latent Space Network Model (HLSM) for ensemble of networks as described in Sweet, Thomas & Junker (2013). <DOI:10.3102/1076998612458702>.
Imports: MASS, coda, igraph, grDevices, graphics, methods, abind, stats

Packaged: 2018-05-26 19:41:04 UTC; samrachanaadhikari

Title: Hierarchical Model-Based Estimation Approach
person("Svetlana", "Saarela", role = c("cre", "aut"), email = "admin@svetlanasaarela.com"),
person("Zhiqiang", "Yang", role = "aut", email='zhiqiangyang@fs.fed.us'),
person("Wilmer", "Prentius", role = "ctb")
Description: For estimation of a variable of interest using two sources of auxiliary information available in a nested structure. For reference see Saarela et al. (2016)<doi:10.1007/s13595-016-0590-1> and Saarela et al. (2018) <doi:10.3390/rs10111832>.
SummaryHMB-class.R ghmb.R gtsmb.R hmb.R tsmb.R

Title: Read HMD and HFD Data from the Web
Author: Tim Riffe, Carl Boe, Josh Goldstein
Description: Utilities for reading data from the Human Mortality Database (<www.mortality.org>), Human Fertility Database (<www.humanfertility.org>), and similar databases from the web or locally into an R session as data.frame objects. These are the two most widely used sources of demographic data to study basic demographic change, trends, and develop new demographic methods. Other supported databases at this time include the Human Fertility Collection (<http://www.fertilitydata.org/>), The Japanese Mortality Database (<http://www.ipss.go.jp/p-toukei/JMD>), and the Canadian Human Mortality Database (<http://www.bdlc.umontreal.ca/chmd/>). Arguments and data are standardized.
Collate: 'age2int.R' 'HFDutils.R' 'HMDutils.R' 'readHFD.R' 'readHMD.R'