marked: Mark-Recapture Analysis for Survival and Abundance Estimation
Version 1.1.13

Functions for fitting various models to capture-recapture data including fixed and mixed-effects Cormack-Jolly-Seber(CJS) for survival estimation and POPAN structured Jolly-Seber models for abundance estimation. Includes a CJS models that concurrently estimates and corrects for tag loss. Hidden Markov model (HMM) implementations of CJS and multistate models with and without state uncertainty.

AuthorJeff Laake <jeff.laake@noaa.gov>, Devin Johnson <devin.johnson@noaa.gov>, Paul Conn <paul.conn@noaa.gov>
Date of publication2016-12-06 18:27:17
MaintainerJeff Laake <jefflaake@gmail.com>
LicenseGPL (>= 2)
Version1.1.13
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("marked")

Popular man pages

crm: Capture-recapture model fitting function
dipper: Dipper capture-recapture data
js.hessian: Compute variance-covariance matrix for fitted JS model
mscjs: Fitting function for Multistate CJS models
mvmscjs: Fitting function for Multivariate Multistate CJS with...
setup_tmb: TMB setup
tagloss: Tag loss example
See all...

All man pages Function index File listing

Man pages

backward_prob: Computes backward probabilities
cjs: Fitting function for CJS models
cjs.accumulate: Accumulates common capture history values
cjs_delta: HMM Initial state distribution functions
cjs_gamma: HMM Transition matrix functions
cjs.hessian: Compute variance-covariance matrix for fitted CJS model
cjs.initial: Computes starting values for CJS p and Phi parameters
cjs.lnl: Likelihood function for Cormack-Jolly-Seber model
cjs_tmb: Fitting function for CJS models
coef.crm: Extract coefficients
compute_matrices: Compute HMM matrices
compute.real: Compute estimates of real parameters
convert.link.to.real: Convert link values to real parameters
create.dm: Creates a design matrix for a parameter
create.dmdf: Creates a dataframe with all the design data for a particular...
create.fixed.matrix: Create parameters with fixed matrix
create.links: Creates a 0/1 vector for real parameters with sin link
crm: Capture-recapture model fitting function
crm.wrapper: Automation of model runs
deriv_inverse.link: Derivatives of inverse of link function (internal use)
dipper: Dipper capture-recapture data
dmat_hsmm2hmm: Create expanded state-dependent observation matrix for HMM...
fix.parameters: Fixing real parameters in crm models
function.wrapper: Utility extract functions
global_decode: Global decoding of HMM
hmmDemo: HMM computation demo functions
HMMLikelihood: Hidden Markov Model likelihood functions
hsmm2hmm: Compute transition matrix for HMM from HSMM
initiate_pi: Setup fixed values for pi in design data
inverse.link: Inverse link functions (internal use)
js: Fitting function for Jolly-Seber model using Schwarz-Arnason...
js.accumulate: Accumulates common capture history values
js.hessian: Compute variance-covariance matrix for fitted JS model
js.lnl: Likelihood function for Jolly-Seber model using...
local_decode: Local decoding of HMM
make.design.data: Create design dataframes for crm
merge_design.covariates: Merge time (occasion) and/or group specific covariates into...
mixed.model.admb: Mixed effect model contstruction
mscjs: Fitting function for Multistate CJS models
mstrata: Multistrata example data
mvmscjs: Fitting function for Multivariate Multistate CJS with...
mvms_design_data: Multivariate Multistate (mvms) Design Data
mvms_dmat: HMM Observation Probability matrix functions
omega: Compute 1 to k-step transition proportions
Phi.mean: Various utility parameter summary functions
predict.crm: Compute estimates of real parameters
print.crm: Print model results
print.crmlist: Print model table from model list
probitCJS: Perform MCMC analysis of a CJS model
process.ch: Process release-recapture history data
process.data: Process encounter history dataframe for MARK analysis
proc.form: Mixed effect model formula parser Parses a mixed effect model...
resight.matrix: Various utility functions
R_HMMLikelihood: Hidden Markov Model Functions
sealions: Multivariate State example data
set.fixed: Set fixed real parameter values in ddl
set.initial: Set initial values
set_mvms: Multivariate Multistate (mvms) Specification
set.scale: Scaling functions
setup_admb: ADMB setup
setup.model: Defines model specific parameters (internal use)
setup.parameters: Setup parameter structure specific to model (internal use)
setup_tmb: TMB setup
simHMM: Simulates data from Hidden Markov Model
skagit: An example of the Mulstistrata (multi-state) model in which...
splitCH: Split/collapse capture histories
tagloss: Tag loss example
valid.parameters: Determine validity of parameters for a model (internal use)

Functions

Files

inst
inst/cjsre_tmb.cpp
inst/parameters.txt
inst/CITATION
inst/cjsre.tpl
inst/models.txt
inst/mvms.tpl
inst/cjs_tmb.cpp
inst/xmodelm5.cpp
inst/multistate.tpl
inst/cjs_reml.tpl
inst/df1b2gh.cpp
inst/README.txt
inst/df1b2ghmult.cpp
inst/doc
inst/doc/markedVignette.Rnw
inst/doc/markedVignette.pdf
inst/doc/markedVignette.R
inst/minfil.cpp
inst/cjs.tpl
src
src/cjs2tlgam.f
src/Makevars
src/bayesCR.cpp
src/ms2gamma.f
src/hmm_like.f
src/cjsdmat.f
src/cjs2tldmat.f
src/cjs1tldmat.f
src/mvmsdmat.f
src/cjs1tlgam.f
src/msdmat.f
src/Makevars.win
src/umsdmat.f
src/cjsgamma.f
src/ums2dmat.f
src/cjs.f
src/msgamma.f
NAMESPACE
demo
demo/00Index
demo/tests.r
NEWS
data
data/mstrata.rda
data/dipper.rda
data/skagit.rda
data/tagloss.rda
data/sealions.rda
R
R/mixed.model.r
R/predict.crm.r
R/admbutils.R
R/proc.formula.r
R/js.r
R/js.accumulate.R
R/js.lnl.r
R/compute.real.R
R/RHMMLikelihood.r
R/print.crm.r
R/cjs.lnl.r
R/setup.parameters.R
R/convert.link.to.real.r
R/create.links.r
R/Observation_functions.r
R/mscjs.r
R/set.initial.r
R/create.dmdf.R
R/crm.wrapper.R
R/summary.fcts.R
R/cjs.hessian.r
R/process.data.R
R/js.hessian.R
R/Transition_functions.r
R/setup.model.R
R/splitCH.R
R/probitCJS.R
R/utility.R
R/valid.parameters.R
R/cjs.initial.R
R/extract.fcts.r
R/cjs.accumulate.R
R/inverse.link.R
R/fix.parameters.r
R/simplify.r
R/make.design.data.R
R/InitialDistribution_functions.r
R/set.fixed.R
R/hsmm2hmm.r
R/scale.r
R/HMMLikelihood.r
R/cjs.R
R/cjs_tmb.R
R/HMMutilities.r
R/crm.R
R/simHMM.r
R/create.dm.R
R/hmmDemo.r
R/set_mvms.r
R/deriv.inverse.link.R
R/process.ch.R
R/merge.design.covariates.r
R/omega.r
R/marked-package.R
R/coef.r
R/mvmscjs.R
R/zzz.R
vignettes
vignettes/markedVignette.Rnw
vignettes/markedWriteUpBib.bib
MD5
build
build/vignette.rds
DESCRIPTION
man
man/merge_design.covariates.Rd
man/hmmDemo.Rd
man/valid.parameters.Rd
man/compute_matrices.Rd
man/function.wrapper.Rd
man/process.data.Rd
man/set_mvms.Rd
man/cjs_delta.Rd
man/process.ch.Rd
man/mstrata.Rd
man/mvms_design_data.Rd
man/backward_prob.Rd
man/local_decode.Rd
man/hsmm2hmm.Rd
man/setup.model.Rd
man/probitCJS.Rd
man/tagloss.Rd
man/inverse.link.Rd
man/cjs_tmb.Rd
man/js.hessian.Rd
man/mvmscjs.Rd
man/create.dm.Rd
man/deriv_inverse.link.Rd
man/set.scale.Rd
man/global_decode.Rd
man/js.accumulate.Rd
man/HMMLikelihood.Rd
man/create.links.Rd
man/predict.crm.Rd
man/cjs.accumulate.Rd
man/dmat_hsmm2hmm.Rd
man/compute.real.Rd
man/proc.form.Rd
man/skagit.Rd
man/make.design.data.Rd
man/omega.Rd
man/convert.link.to.real.Rd
man/mvms_dmat.Rd
man/create.dmdf.Rd
man/setup.parameters.Rd
man/resight.matrix.Rd
man/print.crmlist.Rd
man/cjs.Rd
man/create.fixed.matrix.Rd
man/set.initial.Rd
man/setup_tmb.Rd
man/simHMM.Rd
man/set.fixed.Rd
man/cjs.lnl.Rd
man/js.Rd
man/cjs.initial.Rd
man/splitCH.Rd
man/sealions.Rd
man/js.lnl.Rd
man/R_HMMLikelihood.Rd
man/cjs.hessian.Rd
man/mixed.model.admb.Rd
man/crm.wrapper.Rd
man/cjs_gamma.Rd
man/fix.parameters.Rd
man/Phi.mean.Rd
man/coef.crm.Rd
man/mscjs.Rd
man/setup_admb.Rd
man/dipper.Rd
man/crm.Rd
man/initiate_pi.Rd
man/print.crm.Rd
marked documentation built on May 19, 2017, 3:10 p.m.

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