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marked (version 1.2.6)

Mark-Recapture Analysis for Survival and Abundance Estimation

Description

Functions for fitting various models to capture-recapture data including mixed-effects Cormack-Jolly-Seber(CJS) and multistate models and the multi-variate state model structure for survival estimation and POPAN structured Jolly-Seber models for abundance estimation. There are also Hidden Markov model (HMM) implementations of CJS and multistate models with and without state uncertainty and a simulation capability for HMM models.

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Version

Install

install.packages('marked')

Monthly Downloads

1,043

Version

1.2.6

License

GPL (>= 2)

Maintainer

Jeff Laake

Last Published

December 9th, 2019

Functions in marked (1.2.6)

Phi.mean

Various utility parameter summary functions
Paradise_shelduck

Mulstistate Live-Dead Paradise Shelduck Data
HMMLikelihood

Hidden Markov Model likelihood functions
compute_matrices

Compute HMM matrices
crm.wrapper

Automation of model runs
compute_real

Compute estimates of real parameters
R_HMMLikelihood

Hidden Markov Model Functions
cjs.initial

Computes starting values for CJS p and Phi parameters
create.dm

Creates a design matrix for a parameter
cjs.hessian

Compute variance-covariance matrix for fitted CJS model
convert.link.to.real

Convert link values to real parameters
global_decode

Global decoding of HMM
cjs_tmb

Fitting function for CJS models
cjs.accumulate

Accumulates common capture history values
hmmDemo

HMM computation demo functions
coef.crm

Extract coefficients
deriv_inverse.link

Derivatives of inverse of link function (internal use)
create.dmdf

Creates a dataframe with all the design data for a particular parameter in a crm model
hsmm2hmm

Compute transition matrix for HMM from HSMM
js.lnl

Likelihood function for Jolly-Seber model using Schwarz-Arnason POPAN formulation
fix.parameters

Fixing real parameters in crm models
create.fixed.matrix

Create parameters with fixed matrix
function.wrapper

Utility extract functions
js.accumulate

Accumulates common capture history values
create.links

Creates a 0/1 vector for real parameters with sin link
crm

Capture-recapture model fitting function
js.hessian

Compute variance-covariance matrix for fitted JS model
local_decode

Local decoding of HMM
mvmscjs_tmb

TMB version: Fitting function for Multivariate Multistate CJS with uncertainty models
initiate_pi

Setup fixed values for pi in design data
cjs_delta

HMM Initial state distribution functions
cjs_gamma

HMM Transition matrix functions
dipper

Dipper capture-recapture data
dmat_hsmm2hmm

Create expanded state-dependent observation matrix for HMM from HSMM
mvms_dmat

HMM Observation Probability matrix functions
omega

Compute 1 to k-step transition proportions
inverse.link

Inverse link functions (internal use)
js

Fitting function for Jolly-Seber model using Schwarz-Arnason POPAN formulation
mixed.model.admb

Mixed effect model contstruction
make.design.data

Create design dataframes for crm
process.data

Process encounter history dataframe for MARK analysis
mvmscjs

Fitting function for Multivariate Multistate CJS with uncertainty models
set.initial

Set initial values
set.scale

Scaling functions
resight.matrix

Various utility functions
msld_tmb

Fitting function for Multistate CJS live-dead models with TMB
process.ch

Process release-recapture history data
proc.form

Mixed effect model formula parser Parses a mixed effect model in the lme4 structure of ~fixed +(re1|g1) +...+(ren|gn)
skagit

An example of the Mulstistrata (multi-state) model in which states are routes taken by migrating fish.
mscjs_tmb

Fitting function for Multistate CJS models with TMB
merge_design.covariates

Merge time (occasion) and/or group specific covariates into design data
sealions

Multivariate State example data
mscjs

Fitting function for Multistate CJS models
print.crmlist

Print model table from model list
set.fixed

Set fixed real parameter values in ddl
set_mvms

Multivariate Multistate (mvms) Specification
splitCH

Split/collapse capture histories
setup.model

Defines model specific parameters (internal use)
setup.parameters

Setup parameter structure specific to model (internal use)
setup_admb

ADMB setup
probitCJS

Perform MCMC analysis of a CJS model
tagloss

Tag loss example
valid.parameters

Determine validity of parameters for a model (internal use)
predict.crm

Compute estimates of real parameters
mvms_design_data

Multivariate Multistate (mvms) Design Data
mstrata

Multistrata example data
print.crm

Print model results
setup_tmb

TMB setup
simHMM

Simulates data from Hidden Markov Model
cjs.lnl

Likelihood function for Cormack-Jolly-Seber model
backward_prob

Computes backward probabilities
cjs_admb

Fitting function for CJS models