LaMa - Latent Markov model toolbox

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Version

Install

install.packages('LaMa')

Version

2.0.5

License

GPL-3

Maintainer

Jan-Ole Koslik

Last Published

June 15th, 2025

Functions in LaMa (2.0.5)

make_matrices_dens

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

forward_s

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

logLik.qremlModel

Extract log-likelihood from qremlModel object

gamma2

Reparametrised gamma distribution

forward_sp

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

pseudo_res_discrete

Calculate pseudo-residuals for discrete-valued observations

forward_p

Forward algorithm with for periodically varying transition probability matrices

pseudo_res

Calculate pseudo-residuals

qreml

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

predict.LaMa_matrices

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

penalty

Computes penalty based on quadratic form

penalty2

Computes generalised quadratic-form penalties

minmax

AD-compatible minimum and maximum functions

nessi

Loch Ness Monster Acceleration Data

forward_phsmm

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

smooth_dens_construct

Build the design and penalty matrices for smooth density estimation

stateprobs

Calculate conditional local state probabilities for homogeneous HMMs

stationary

Compute the stationary distribution of a homogeneous Markov chain

stationary_cont

Compute the stationary distribution of a continuous-time Markov chain

stateprobs_g

Calculate conditional local state probabilities for inhomogeneous HMMs

stateprobs_p

Calculate conditional local state probabilities for periodically inhomogeneous HMMs

qreml_old

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

sdreportMC

Monte Carlo version of sdreport

tpm_g

Build all transition probability matrices of an inhomogeneous HMM

tpm_hsmm

Builds the transition probability matrix of an HSMM-approximating HMM

tpm

Build the transition probability matrix from unconstrained parameter vector

tpm_cont

Calculate continuous time transition probabilities

tpm_emb

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

plot.LaMaResiduals

Plot pseudo-residuals

sdreport_outer

Report uncertainty of the estimated smoothing parameters or variances

pred_matrix

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

skewnorm

Skew normal distribution

stationary_p_sparse

Sparse version of stationary_p

tpm_thinned

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

tpm_phsmm2

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

stationary_p

Periodically stationary distribution of a periodically inhomogeneous Markov chain

stationary_sparse

Sparse version of stationary

trex

T-Rex Movement Data

summary.qremlModel

Summary method for qremlModel objects

trigBasisExp

Compute the design matrix for a trigonometric basis expansion

tpm_ihsmm

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

wrpcauchy

wrapped Cauchy distribution

tpm_hsmm2

Build the transition probability matrix of an HSMM-approximating HMM

tpm_p

Build all transition probability matrices of a periodically inhomogeneous HMM

tpm_phsmm

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

zero_inflate

Zero-inflated density constructer

viterbi

Viterbi algorithm for state decoding in homogeneous HMMs

tpm_emb_g

Build all embedded transition probability matrices of an inhomogeneous HSMM

von Mises distribution

viterbi_p

Viterbi algorithm for state decoding in periodically inhomogeneous HMMs

viterbi_g

Viterbi algorithm for state decoding in inhomogeneous HMMs

cosinor

Evaluate trigonometric basis expansion

forward_ihsmm

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

calc_trackInd

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

ddwell

State dwell-time distributions of periodically inhomogeneous Markov chains

forward

Forward algorithm with homogeneous transition probability matrix

forward_hsmm

Forward algorithm for homogeneous hidden semi-Markov models

LaMa-package

LaMa: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models

dirichlet

Dirichlet distribution

generator

Build the generator matrix of a continuous-time Markov chain

dgmrf2

Reparametrised multivariate Gaussian distribution

forward_g

General forward algorithm with time-varying transition probability matrix

make_matrices

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

gdeterminant

Computes generalised determinant