Hidden Markov Model for Return Time-Series Based on Lambda Distribution

Documentation for package ‘ldhmm’ version 0.1.0

ldhmm-package	ldhmm: A package for HMM using lambda distribution.
ldhmm	Constructor of ldhmm class
ldhmm-class	The ldhmm class
ldhmm.calc_stats_from_obs	Computing the statistics for each state
ldhmm.conditional_prob	Computing the conditional probabilities
ldhmm.decoding	Computing the minus log-likelihood (MLLK)
ldhmm.forecast_prob	Computing the forecast probability distribution
ldhmm.forecast_state	Computing the state forecast
ldhmm.ld_stats	Computes the theoretical statistics per state
ldhmm.log_backward	Computing the log forward and backward probabilities
ldhmm.log_forward	Computing the log forward and backward probabilities
ldhmm.mle	Computing the MLEs
ldhmm.mllk	Computing the minus log-likelihood (MLLK)
ldhmm.n2w	Transforming natural parameters to a linear working parameter array
ldhmm.pseudo_residuals	Computing pseudo-residuals
ldhmm.state_ld	Constructing the ecld objects per state
ldhmm.state_pdf	Computing the PDF per state given the observations
ldhmm.ts_abs_acf	Computing ACF of the absolute value of a time series
ldhmm.ts_log_rtn	Get log-returns from historic prices of an index
ldhmm.viterbi	Computing the global decoding by the Viterbi algorithm
ldhmm.w2n	Transforming working parameter array to natural parameters
numericOrNull-class	The numericOrNull class