LaMa - Latent Markov model toolbox

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Install

install.packages('LaMa')

Monthly Downloads

478

Version

3.1.0

License

MIT + file LICENSE

Maintainer

Jan-Ole Fischer

Last Published

November 9th, 2026

Functions in LaMa (3.1.0)

%sp%

Sparsity-retaining matrix multiplication

logLik.LaMaModel

Extract log-likelihood from LaMaModel object

penalty

Computes penalty based on quadratic form

nessi

Loch Ness Monster Acceleration Data

minmax

AD-compatible minimum and maximum functions

forward_sp

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

predict.LaMa_matrices

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

minmax0_smooth

Smooth approximations to max(x, 0) and min(x, 0)

pred_matrix

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

process_hid_formulas

Process and standardise formulas for the state process of hidden Markov models

print.LaMa_matrices

Print a LaMa_matrices object

modmat

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

plot.LaMaModel

Plot a LaMaModel object

plot.LaMaResiduals

Plot pseudo-residuals

multistart

Optimise an RTMB object from several starting values

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

penalty2

Computes generalised quadratic-form penalties

lama

Build a LaMaModel from an optimised RTMB object

predict.smoothdens

Estimated smooth densities

print.LaMaModel

Print a LaMaModel object

penalty_uni

Penalty approximation of unimodality constraints for univariate smooths

qreml

Automatic smoothness selection for arbitrary statistical models with penalised splines, simple random effects, or tensorproducts

pseudo_res

Calculate pseudo-residuals

sdreportMC

Monte Carlo version of sdreport

residuals.LaMaModel

Pseudo-residuals of a LaMaModel object

scores

Per-observation score contributions

rep_sp

Repeat initial penalty strengths for replicated smooths

qreml_old

Quasi restricted maximum likelihood (qREML) algorithm, previous version

skewnorm

Skew normal distribution

smoothdens

Build the design and penalty matrices for smooth density estimation

stateprobs_g

Calculate conditional local state probabilities for inhomogeneous HMMs

stateprobs_p

Calculate conditional local state probabilities for periodically inhomogeneous HMMs

simulate.LaMaModel

Simulate from a fitted model

sdreport_outer

Report uncertainty of the estimated smoothing parameters or variances

smooth_dens_construct

Build the design and penalty matrices for smooth density estimation

stationary_ct

Compute the stationary distribution of a continuous-time Markov chain

stationary

Compute the stationary distribution of a homogeneous Markov chain

tpm_hsmm

Builds the transition probability matrix of an HSMM-approximating HMM

stationary_p_sparse

Sparse version of stationary_p

stationary_p

Periodically stationary distribution of a periodically inhomogeneous Markov chain

tpm_g2

Build all transition probability matrices of an inhomogeneous HMM

tpm_emb

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

statedens

State-dependent densities of one data stream

stateprobs

Calculate conditional local state probabilities in HMMs

tpm_ct

Calculate continuous time transition probabilities

stationary_sparse

Sparse version of stationary

tpm_g

Build all transition probability matrices of an inhomogeneous HMM

tpm_emb_g

Build all embedded transition probability matrices of an inhomogeneous HSMM

tpm_phsmm2

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

tpm_thinned

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

tpm_hsmm2

Build the transition probability matrix of an HSMM-approximating HMM

summary.LaMaModel

Summary of a LaMaModel object

tpm_ihsmm

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

trex

T-Rex Movement Data

trigBasisExp

Compute the design matrix for a trigonometric basis expansion

zero_inflate

Zero-inflated density constructer

wrpcauchy

Wrapped Cauchy distribution

Von Mises distribution

viterbi_g

Viterbi algorithm for state decoding in inhomogeneous HMMs

viterbi

Viterbi algorithm for state decoding in HMMs

vcov.LaMaModel

Variance-covariance matrix of a LaMaModel object

viterbi_p

Viterbi algorithm for state decoding in periodically inhomogeneous HMMs

tpm_phsmm

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

tpm_p

Build all transition probability matrices of a periodically inhomogeneous HMM

tpm

Build the transition probability matrix from unconstrained parameter vector

summary.qremlModel

Summary of a qremlModel object

coef.LaMaModel

Estimated parameters of a LaMaModel object

ddwell

State dwell-time distributions of periodically inhomogeneous Markov chains

dgmrf2

Reparametrised multivariate Gaussian distribution

LaMaColors

Generate a colour-blind-friendly palette

LaMa-package

LaMa: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models

forward_g

Forward algorithm with time-varying transition probability matrix

forward

Forward algorithm to calculate the HMM log-likelihood

cosinor

Trigonometric basis expansion

MCreport

Sample parameters from approximate Gaussian posterior distribution

generator

Build the generator matrix of a continuous-time Markov chain

generator_g

Build generator matrices of a continuous-time Markov chain

forward_p

Forward algorithm with for periodically varying transition probability matrices

calc_trackInd

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

forward_ihsmm

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

forward_s

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

forward_hsmm

Forward algorithm for homogeneous hidden semi-Markov models

gamma2

Reparametrised gamma distribution

gdeterminant

Computes generalised determinant