Create Credit State Migration (Transition) Matrices
c(person(given = "Michael",
family = "Thomas",
role = c("aut", "cre"),
email = "mthomas@ketchbrookanalytics.com"),
person(given = "Brad",
family = "Lindblad",
role = "ctb",
email = "bradley.lindblad@gmail.com"))
Tools to help convert credit risk data at two time points
into traditional credit state migration (aka, "transition") matrices.
At a higher level, 'migrate' is intended to help an analyst understand
how risk moved in their credit portfolio over a time interval.
References to this methodology include:
1. Schuermann, T. (2008) <doi:10.1002/9780470061596.risk0409>.
2. Perederiy, V. (2017) <arXiv:1708.00062>.
Michael Thomas [aut, cre],
Brad Lindblad [ctb]

dplyr (>= 1.0.7), tidyr (>= 1.1.0), tibble (>= 3.0.1), rlang,
utils, magrittr

Lajos Bálint <balint@demografia.hu> and Gergely Daróczi
<daroczig@rapporter.net>
This package provides various indices, like Crude
Migration Rate, different Gini indices or the Coefficient of
Variation among others, to show the (un)equality of migration.
'gini.R' 'migration.indices.R' 'crude.R' 'others.R' 'acv.R'

This package provides various indices, like Crude Migration Rate,
different Gini indices or the Coefficient of Variation among others, to
show the (un)equality of migration.
'gini.R' 'migration.indices.R' 'crude.R' 'others.R' 'acv.R'
'graph.R'

Calculate various indices, like Crude Migration Rate,
different Gini indices or the Coefficient of Variation among others, to
show the (un)equality of migration.

Production Rules Based Classification of Migration
c(
person(given = "Leshi",
family = "Chen",
email = "leshi.chen@stats.govt.nz",
role = c("aut", "cre")),
person(given = "Pubudu",
family = "Senanayake",
email = "pubudu.senanayake@stats.govt.nz",
role = c("aut")),
person(given = "Del",
family = "Robinson",
email = "del.robinson@stats.govt.nz",
role = c("aut")),
person("Statistics New Zealand",
role = c("cph")))
Leshi Chen [aut, cre],
Pubudu Senanayake [aut],
Del Robinson [aut],
Statistics New Zealand [cph]
Provides mechanisms for classifying border crossings using a rules-based methodology. The goal of performing this type of classification is to identify any potential long-term migrants.  A long-term migration is defined as a border crossing involving a change in residence status. A border crossing counts as a long-term migration to/from a country if it entails a change from non-residence to residence / residence to non-residence.  The rules-based classification that used to determine a long-term migration is defined by a threshold duration and a test duration, alternatively named window size. Under a 12/16 rule, for instance, the threshold duration is 12 months and the test duration (window size) is 16 months. With a 9/12 rule, the threshold duration is 9 months and the test duration (window size)  is 12 months. For more information about the methodology applied, please visit Stats NZ (2020) <https://www.stats.govt.nz/methods/defining-migrants-using-travel-histories-and-the-1216-month-rule>.
Rcpp (>= 1.0), lubridate (>= 1.7), stringr (>= 1.4), dplyr (>=
0.8), methods, parallel, futile.logger
magrittr, tools, knitr, rmarkdown, testthat
'RcppExports.R' 'check_functions.R' 'plot_mig_hist.R'
'pre_process.R' 'resolve_data.R' 'resolve_data_with_error.R'
'run_rbc.R' 'utility_functions.R' 'migrbc.R'