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LaMa - Latent Markov model toolbox

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Version

Install

install.packages('LaMa')

Monthly Downloads

153

Version

2.0.4

License

GPL-3

Maintainer

Jan-Ole Koslik

Last Published

June 5th, 2025

Functions in LaMa (2.0.4)

calc_trackInd

Calculate the index of the first observation of each track based on an ID variable
make_matrices

Build the design and the penalty matrix for models involving penalised splines based on a formula and a data set
forward_p

Forward algorithm with for periodically varying transition probability matrices
forward_phsmm

Forward algorithm for hidden semi-Markov models with periodically inhomogeneous state durations and/ or conditional transition probabilities
make_matrices_dens

Build a standardised P-Spline design matrix and the associated P-Spline penalty matrix
LaMa-package

LaMa: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models
penalty2

Computes generalised quadratic-form penalties
forward_ihsmm

Forward algorithm for hidden semi-Markov models with inhomogeneous state durations and/ or conditional transition probabilities
penalty

Computes penalty based on quadratic form
qreml

Quasi restricted maximum likelihood (qREML) algorithm for models with penalised splines or simple i.i.d. random effects
qreml_old

Quasi restricted maximum likelihood (qREML) algorithm for models with penalised splines or simple i.i.d. random effects
pseudo_res

Calculate pseudo-residuals
sdreportMC

Monte Carlo version of sdreport
forward_s

Forward algorithm for hidden semi-Markov models with homogeneous transition probability matrix
pseudo_res_discrete

Calculate pseudo-residuals for discrete-valued observations
sdreport_outer

Report uncertainty of the estimated smoothing parameters or variances
forward_sp

Forward algorithm for hidden semi-Markov models with periodically varying transition probability matrices
stateprobs_p

Calculate conditional local state probabilities for periodically inhomogeneous HMMs
stationary

Compute the stationary distribution of a homogeneous Markov chain
pred_matrix

Build the prediction design matrix based on new data and model_matrices object created by make_matrices
predict.LaMa_matrices

Build the prediction design matrix based on new data and model_matrices object created by make_matrices
stationary_cont

Compute the stationary distribution of a continuous-time Markov chain
skewnorm

Skew normal distribution
smooth_dens_construct

Build the design and penalty matrices for smooth density estimation
tpm

Build the transition probability matrix from unconstrained parameter vector
stationary_p

Periodically stationary distribution of a periodically inhomogeneous Markov chain
tpm_cont

Calculate continuous time transition probabilities
nessi

Loch Ness Monster Acceleration Data
minmax

AD-compatible minimum and maximum functions
stationary_p_sparse

Sparse version of stationary_p
tpm_thinned

Compute the transition probability matrix of a thinned periodically inhomogeneous Markov chain.
viterbi_g

Viterbi algorithm for state decoding in inhomogeneous HMMs
summary.qremlModel

Summary method for qremlModel objects
stateprobs

Calculate conditional local state probabilities for homogeneous HMMs
trex

T-Rex Movement Data
tpm_hsmm

Builds the transition probability matrix of an HSMM-approximating HMM
tpm_g

Build all transition probability matrices of an inhomogeneous HMM
tpm_emb_g

Build all embedded transition probability matrices of an inhomogeneous HSMM
stateprobs_g

Calculate conditional local state probabilities for inhomogeneous HMMs
tpm_hsmm2

Build the transition probability matrix of an HSMM-approximating HMM
viterbi

Viterbi algorithm for state decoding in homogeneous HMMs
wrpcauchy

wrapped Cauchy distribution
zero_inflate

Zero-inflated density constructer
vm

von Mises distribution
tpm_emb

Build the embedded transition probability matrix of an HSMM from unconstrained parameter vector
trigBasisExp

Compute the design matrix for a trigonometric basis expansion
tpm_phsmm2

Build all transition probability matrices of an periodic-HSMM-approximating HMM
tpm_phsmm

Builds all transition probability matrices of an periodic-HSMM-approximating HMM
tpm_ihsmm

Builds all transition probability matrices of an inhomogeneous-HSMM-approximating HMM
stationary_sparse

Sparse version of stationary
tpm_p

Build all transition probability matrices of a periodically inhomogeneous HMM
viterbi_p

Viterbi algorithm for state decoding in periodically inhomogeneous HMMs
dgmrf2

Reparametrised multivariate Gaussian distribution
cosinor

Evaluate trigonometric basis expansion
forward

Forward algorithm with homogeneous transition probability matrix
dirichlet

Dirichlet distribution
forward_hsmm

Forward algorithm for homogeneous hidden semi-Markov models
forward_g

General forward algorithm with time-varying transition probability matrix
ddwell

State dwell-time distributions of periodically inhomogeneous Markov chains
logLik.qremlModel

Extract log-likelihood from qremlModel object
generator

Build the generator matrix of a continuous-time Markov chain
gamma2

Reparametrised gamma distribution
gdeterminant

Computes generalised determinant