Package: fibre 0.0.0.9000
fibre: Fast Evolutionary Trait Modelling on Phylogenies using Branch Regression Models
Implements Phylogenetic Branch Regression models which allow for flexible and versatile models of evolution along a phylogeny. The model can be used to detect shifts in rates of evolution along branches. The model uses a continuous and linear model structure and so can be easily combined with other non-phylogenetic statistical structures, as long as they are implemented using the R package INLA. One major uses of this are to condition on phylogeny in a standard regression between two traits, thus 'accounting' for phylogenetic structure in the response variable, similar to how pgls is used but allowing for a more flexible phylogenetic model. This also allows the phylogenetic model to be combined with the spatial models that INLA excels at (and with comparable flexibility to those spatial models).
Authors:
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fibre.pdf |fibre.html✨
fibre/json (API)
# Install 'fibre' in R: |
install.packages('fibre', repos = c('https://rdinnager.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rdinnager/fibre/issues
Last updated 12 months agofrom:f62fd4a6f0. Checks:OK: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 01 2024 |
R-4.5-win | WARNING | Nov 01 2024 |
R-4.5-linux | WARNING | Nov 01 2024 |
R-4.4-win | WARNING | Nov 01 2024 |
R-4.4-mac | WARNING | Nov 01 2024 |
R-4.3-win | WARNING | Nov 01 2024 |
R-4.3-mac | WARNING | Nov 01 2024 |
Exports::=.data%>%as_labelas_nameaugmentautoplotbrebre_brownianbre_second_orderdefault_cameradefault_lightenquoenquosevo_autodecoderfibrefibre_formula_blueprintget_acesget_camera_positionget_ratesget_tcesget_tipsglanceload_bird_beak_modelload_modelresdf_netsimulate_traitstidy
Dependencies:apeaplotassertthatbase64encbitbit64callrclassclassIntcliclusterGenerationcodacodetoolscolorspacecombinatcorocorpcorcpp11cubatureDBIDEoptimdescdigestdoParalleldplyre1071ellipsisevaluateexpmfansifarverfastmapfastmatchfmesherforeachfsgenericsggfunggplot2ggplotifyggtreeglmnetgluegridGraphicsgtablehardhathighrhtmltoolsigraphinlabruisobanditeratorsivsjsonliteKernSmoothknitrlabelinglatticelazyevallifecyclemagrittrmapsMASSMatrixMatrixModelsMCMCglmmmgcvmnormtmunsellnlmenumDerivoptimParallelpatchworkphangornphyfphytoolspillarpkgconfigplyrprocessxproxypspurrrquadprogR6RColorBrewerRcppRcppEigenreprrlangs2safetensorsscalesscatterplot3dsfshapeskimrspstringistringrsurvivaltensorAterratibbletidyrtidyselecttidytreetorchtreeiounitsutf8vctrsviridisLitewithrwkxfunyamlyulab.utilszeallot
An Evolutionary Autodecoder Model with {fibre}
Rendered from_evo_autodecoder.Rmd
usingknitr::rmarkdown
on Nov 01 2024.Last update: 2022-11-09
Started: 2022-11-09
Getting Started with {fibre}
Rendered fromfibre.Rmd
usingknitr::rmarkdown
on Nov 01 2024.Last update: 2022-11-12
Started: 2022-11-09
Miscellaneous Stuff
Rendered from_misc.Rmd
usingknitr::rmarkdown
on Nov 01 2024.Last update: 2022-11-15
Started: 2022-11-15
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Specify a branch length (random) effect | bre |
Specify a branch length (random) effect for a Brownian motion model | bre_brownian |
Specify a branch length (random) effect for a 'Second Order' Brownian motion model | bre_second_order |
Create a Evolutionary Autodecoder Model | evo_autodecoder |
Fit a 'fibre' | fibre fibre.data.frame fibre.default fibre.formula fibre.matrix fibre.recipe |
Title | get_aces |
Title | get_rates |
Title | get_tces |
Title | get_tips |
Load a model | load_model |
Predict from a 'fibre' | predict.fibre |
Specify a random effect | re |
A signed distance field based neural network model for generating 3d shapes | sdf_net |
Function to simulate continuous trait value histories on a phylogeny. | simulate_traits |
Tidy Model Results | tidy.fibre |