import from the 'Familias' software (Egeland et al. (2000)

Imports: pedprobr (>= 0.3), ribd, pedmut, maxLik, glue

Imports: pedprobr (>= 0.4), ribd, pedmut, maxLik, glue

Imports: pedprobr (>= 0.4), ribd, pedmut, glue

person("Magnus Dehli", "Vigeland", , "m.d.vigeland@medisin.uio.no", role = c("aut", "cre"),
person("Thore", "Egeland", , "thore.egeland@nmbu.no", role = "ctb")
Description: Forensic applications of pedigree analysis, including
likelihood ratios for relationship testing, general relatedness
inference, marker simulation, and power analysis. General computation
of exclusion powers is based on Egeland et al. (2014)
specifically with family reunion cases, implementing and developing
novelty of 'forrel' is the ability to model background inbreeding in
forensic pedigree computations.  This can have significant impact in
applications, as exemplified in Vigeland and Egeland (2019)
<doi:10.1016/j.fsigss.2019.10.175>. 'forrel' is part of the ped suite,
a collection of packages for pedigree analysis. In particular,
'forrel' imports 'pedtools' for creating and manipulating pedigrees
and markers, 'pedprobr' for likelihood computations, and 'pedmut' for
mutation modelling.  Pedigree data may be created from scratch, or
loaded from text files. Data import from the 'Familias' software
Imports: glue, pedmut, pedprobr (>= 0.4), ribd (>= 1.3.0)
Suggests: ggplot2, poibin, scales, testthat

Title: Outlier Diagnostics for Some Linear Effects and Linear Mixed
Description: Identifies potential data outliers and their impact on estimates and analyses.
Uses the forward search approach of Atkinson and Riani, "Robust Diagnostic Regression
Analysis", (2000,<ISBN: o-387-95017-6>) to prepare descriptive statistics of a dataset
that is to be analyzed by stats::lm() or nlme::lme().  Includes graphics functions to

that is to be analyzed by stats::lm(), stats::glm(), or nlme::lme().  Includes graphics
functions to display the descriptive statistics.

email = "wrf343@flowervalleyconsulting.com", role = c("aut", "cre"))
Description: Identifies potential data outliers and their impact on estimates and analyses. Uses the forward search approach of Atkinson and Riani, "Robust Diagnostic Regression Analysis", 2000,<ISBN: o-387-95017-6>) to prepare descriptive statistics of a dataset that is to be analyzed by stats::lm(), stats::glm(), or nlme::lme().  Includes graphics functions to display the descriptive statistics.