HMMLikelihood           Hidden Markov Model likelihood functions
Paradise_shelduck       Mulstistate Live-Dead Paradise Shelduck Data
Phi.mean                Various utility parameter summary functions
R_HMMLikelihood         Hidden Markov Model Functions
backward_prob           Computes backward probabilities
cjs.accumulate          Accumulates common capture history values
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_admb                Fitting function for CJS models
cjs_delta               HMM Initial state distribution functions
cjs_gamma               HMM Transition matrix functions
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 parameter in a crm model
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 from HSMM
fix.parameters          Fixing real parameters in crm models
function.wrapper        Utility extract functions
global_decode           Global decoding of HMM
hmmDemo                 HMM computation demo 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 POPAN formulation
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
                        Schwarz-Arnason POPAN formulation
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 design data
mixed.model.admb        Mixed effect model contstruction
mscjs                   Fitting function for Multistate CJS models
mscjs_tmb               Fitting function for Multistate CJS models with
                        TMB
msld_tmb                Fitting function for Multistate CJS live-dead
                        models with TMB
mstrata                 Multistrata example data
mvms_design_data        Multivariate Multistate (mvms) Design Data
mvms_dmat               HMM Observation Probability matrix functions
mvmscjs                 Fitting function for Multivariate Multistate
                        CJS with uncertainty models
mvmscjs_tmb             TMB version: Fitting function for Multivariate
                        Multistate CJS with uncertainty models
omega                   Compute 1 to k-step transition proportions
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
proc.form               Mixed effect model formula parser Parses a
                        mixed effect model in the lme4 structure of
                        ~fixed +(re1|g1) +...+(ren|gn)
process.ch              Process release-recapture history data
process.data            Process encounter history dataframe for MARK
                        analysis
resight.matrix          Various utility 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.model             Defines model specific parameters (internal
                        use)
setup.parameters        Setup parameter structure specific to model
                        (internal use)
setup_admb              ADMB setup
setup_tmb               TMB setup
simHMM                  Simulates data from Hidden Markov Model
skagit                  An example of the Mulstistrata (multi-state)
                        model in which states are routes taken by
                        migrating fish.
smsld_tmb               Fitting function for Multistate CJS live-dead
                        models with TMB
splitCH                 Split/collapse capture histories
tagloss                 Tag loss example
valid.parameters        Determine validity of parameters for a model
                        (internal use)
