Fit Hidden Markov Models using Template Model Builder
Read formula with as.character without splitting
Transforms matrix to dgTMatrix
Create block diagonal matrix (safe version)
Check values in vector are contiguous
Grid of covariates
R6 class for probability distribution
Density function of von Mises distribution
Density function of wrapped Cauchy distribution
Find s(, bs = "re") terms in formula
Generalized matrix determinant
R6 class for hidden Markov model
hmmTMB colour palette
hmmTMB: Fit Hidden Markov Models using Template Model Builder
Multivarite inverse logit function
Check if number of whole number
logLik function for SDE objects
Log of sum of exponentials
Make covariance matrix from standard deviations and correlations
Process formulas and store in nested list
Create model matrices
R6 class for HMM hidden process model
Multivariate logit function
Multivariate Normal inverse link function
Multivariate Normal link function
Fill in NAs
R6 class for HMM observation model
Get covariance matrix from precision matrix
Solve for positive root of quadratic ax^2 + bx + c = 0 when it exists
Sample from von Mises distribution
Sample from wrapped Cauchy distribution
Strip comments marked with a hash from a character vector
Update a model to a new model by changing one formula
Fitting hidden Markov models using automatic differentiation and Laplace approximation, allowing for fast inference and flexible covariate effects (including random effects and smoothing splines) on model parameters. The package is described by Michelot (2022) <doi:10.48550/arXiv.2211.14139>.