Fast Numerical Maximum Likelihood Estimation for Latent Markov Models

[Up] [Top]

Documentation for package ‘LaMa’ version 3.0.0

Help Pages

C D F G L M N P Q R S T V W Z misc

-- C --

calc_trackInd Calculate the index of the first observation of each track based on an ID variable
cosinor Trigonometric basis expansion

-- D --

ddwell State dwell-time distributions of periodically inhomogeneous Markov chains
dgamma2 Reparametrised gamma distribution
dgmrf2 Reparametrised multivariate Gaussian distribution
dskewnorm Skew normal distribution
dvm Von Mises distribution
dwrpcauchy Wrapped Cauchy distribution

-- F --

forward Forward algorithm to calculate the HMM log-likelihood
forward_g Forward algorithm with time-varying transition probability matrix
forward_hsmm Forward algorithm for homogeneous hidden semi-Markov models
forward_ihsmm Forward algorithm for hidden semi-Markov models with inhomogeneous state durations and/ or conditional transition probabilities
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
forward_s Forward algorithm for hidden semi-Markov models with homogeneous transition probability matrix
forward_sp Forward algorithm for hidden semi-Markov models with periodically varying transition probability matrices

-- G --

gamma2 Reparametrised gamma distribution
gdeterminant Computes generalised determinant
generator Build the generator matrix of a continuous-time Markov chain
generator_g Build generator matrices of a continuous-time Markov chain

-- L --

lama Build a 'LaMaModel' from an optimised 'RTMB' object
LaMaColors Generate a colour-blind-friendly palette
logLik.LaMaModel Extract log-likelihood from LaMaModel object

-- M --

make_matrices Build the design and the penalty matrix for models involving penalised splines based on a formula and a data set
make_matrices_dens Build a standardised P-Spline design matrix and the associated P-Spline penalty matrix
max0_smooth Smooth approximations to max(x, 0) and min(x, 0)
max2 AD-compatible minimum and maximum functions
MCreport Sample parameters from approximate Gaussian posterior distribution
min0_smooth Smooth approximations to max(x, 0) and min(x, 0)
min2 AD-compatible minimum and maximum functions
minmax AD-compatible minimum and maximum functions
minmax0_smooth Smooth approximations to max(x, 0) and min(x, 0)
modmat Build the design and the penalty matrix for models involving penalised splines based on a formula and a data set
multistart Optimise an 'RTMB' object from several starting values

-- N --

nessi Loch Ness Monster Acceleration Data

-- P --

penalty Computes penalty based on quadratic form
penalty2 Computes generalised quadratic-form penalties
penalty_uni Penalty approximation of unimodality constraints for univariates smooths
pgamma2 Reparametrised gamma distribution
plot.LaMaModel Plot a 'LaMaModel' object
plot.LaMaResiduals Plot pseudo-residuals
predict.LaMa_matrices Build the prediction design matrix based on new data and model_matrices object created by 'modmat'
predict.smoothdens Estimated smooth densities
pred_matrix Build the prediction design matrix based on new data and model_matrices object created by 'modmat'
print.LaMaModel Print a 'LaMaModel' object
print.LaMa_matrices Print a 'LaMa_matrices' object
print.summary.LaMaModel Summary of a 'LaMaModel' object
print.summary.qremlModel Summary of a 'qremlModel' object
process_hid_formulas Process and standardise formulas for the state process of hidden Markov models
pseudo_res Calculate pseudo-residuals
pskewnorm Skew normal distribution
pvm Von Mises distribution

-- Q --

qgamma2 Reparametrised gamma distribution
qreml Automatic smoothness selection for arbitrary statistical models with penalised splines, simple random effects, or tensorproducts
qreml_old Quasi restricted maximum likelihood (qREML) algorithm, previous version
qskewnorm Skew normal distribution

-- R --

report Build a 'LaMaModel' from an optimised 'RTMB' object
rep_sp Repeat initial penalty strengths for replicated smooths
rgamma2 Reparametrised gamma distribution
rskewnorm Skew normal distribution
rvm Von Mises distribution
rwrpcauchy Wrapped Cauchy distribution

-- S --

scores Per-observation score contributions
sdreportMC Monte Carlo version of 'sdreport'
sdreport_outer Report uncertainty of the estimated smoothing parameters or variances
simulate.LaMaModel Simulate from a fitted model
skewnorm Skew normal distribution
smoothdens Build the design and penalty matrices for smooth density estimation
statedens State-dependent densities of one data stream
stateprobs Calculate conditional local state probabilities in HMMs
stateprobs_g Calculate conditional local state probabilities for inhomogeneous HMMs
stateprobs_p Calculate conditional local state probabilities for periodically inhomogeneous HMMs
stationary Compute the stationary distribution of a homogeneous Markov chain
stationary_cont Compute the stationary distribution of a continuous-time Markov chain
stationary_ct Compute the stationary distribution of a continuous-time Markov chain
stationary_p Periodically stationary distribution of a periodically inhomogeneous Markov chain
stationary_p_sparse Sparse version of 'stationary_p'
stationary_sparse Sparse version of 'stationary'
summary.LaMaModel Summary of a 'LaMaModel' object
summary.qremlModel Summary of a 'qremlModel' object

-- T --

tpm Build the transition probability matrix from unconstrained parameter vector
tpm_cont Calculate continuous time transition probabilities
tpm_ct Calculate continuous time transition probabilities
tpm_emb Build the embedded transition probability matrix of an HSMM from unconstrained parameter vector
tpm_emb_g Build all embedded transition probability matrices of an inhomogeneous HSMM
tpm_g Build all transition probability matrices of an inhomogeneous HMM
tpm_g2 Build all transition probability matrices of an inhomogeneous HMM
tpm_hsmm Builds the transition probability matrix of an HSMM-approximating HMM
tpm_hsmm2 Build the transition probability matrix of an HSMM-approximating HMM
tpm_ihsmm Builds all transition probability matrices of an inhomogeneous-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
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.
trex T-Rex Movement Data
trigBasisExp Compute the design matrix for a trigonometric basis expansion

-- V --

viterbi Viterbi algorithm for state decoding in HMMs
viterbi_g Viterbi algorithm for state decoding in inhomogeneous HMMs
viterbi_p Viterbi algorithm for state decoding in periodically inhomogeneous HMMs
vm Von Mises distribution

-- W --

wrpcauchy Wrapped Cauchy distribution

-- Z --

zero_inflate Zero-inflated density constructer

-- misc --

%sp% Sparsity-retaining matrix multiplication