Imports: ggplot2, graphics, methods, rmarkdown, scales, stats, shiny
Suggests: shinytest, testthat (>= 3.0.0), vdiffr (>= 1.0.0)

disaggregate a low-frequency time-serie with higher frequency time-series,
Imports: graphics, grDevices, methods, RColorBrewer (>= 1.1-2), stats,
Collate: 'bflSmooth.R' 'data.R' 'disaggR.R' 'in.R' 's4register.R'

comment = c(ORCID = "0000-0003-0109-7505","Author, creator and maintener of the package until the version 1.0.2")),
Suggests: knitr, ggplot2 (>= 3.0.0), rmarkdown (>= 2.0.0), shiny (>=
Author: Arnaud Feldmann [aut] (<https://orcid.org/0000-0003-0109-7505>, Author,
creator and maintener of the package until the version 1.0.2),

disaggregate a low-frequency time series with higher frequency time series,
resulting time series is strictly equal to the low-frequency time series within the
benchmarking window. Typically, the low-frequency time series is an annual one,
monthly. See "Methodology of quarterly national accounts", Insee Méthodes
Collate: 'bflSmooth.R' 'data.R' 'disaggR.R' 'utils.R' 'in.R'

person("Anita", "Nandi", email = "anita.k.nandi@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5087-2494")),
person("Tim", "Lucas", email =  "timcdlucas@gmail.com", role = "aut", comment = c(ORCID = "0000-0003-4694-8107")),
person("Rohan", "Arambepola", email = "rarambepola@gmail.com", role = "aut"),
person("Andre", "Python", email = "python.andre@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-8094-7226"))
Description: Fits disaggregation regression models using 'TMB' ('Template Model
Builder'). When the response data are aggregated to polygon level but
the predictor variables are at a higher resolution, these models can be
useful. Regression models with spatial random fields. A useful reference for disaggregation modelling is
Imports: maptools, raster, foreach, sp, parallel, doParallel, rgeos,
splancs, rgdal, Matrix, stats, TMB, dplyr, ggplot2, cowplot,
Suggests: testthat, INLA, knitr, rmarkdown, SpatialEpi
Author: Anita Nandi [aut, cre] (<https://orcid.org/0000-0002-5087-2494>),