Bayesian Inference for DLMS
Functions for filtering, backward sampling and Gibbs sampling for dynamic linear models.
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Ops(<dual>)
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Operators for univariate Dual Numbers |
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clean_results()
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Clean one fixture of scraped results |
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concat()
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Concatenate strings together as a comma-separated list |
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const()
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ctmc_build_rate_matrix()
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ctmc_log_likelihood()
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ctmc_sim_exact()
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Simulate from a continuous time markov chain |
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da_step()
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density_plot()
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Plot a density plot from MCMC output |
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diag_inverse()
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divide()
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dual()
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Representation of a Dual Number |
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effective_size()
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Calculate Effective Sample Size |
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ehmc()
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Hamiltonian Monte Carlo |
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ehmc_helper()
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Empirical Hamiltonian Monte Carlo |
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ehmc_step()
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extract_date()
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Get the date of a fixture |
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find_reasonable_epsilon()
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format_course()
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format_course_name()
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get_course_list()
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Get a list of courses for a given year |
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get_division_results()
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Get Harrier League Results |
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get_harrier_league_results()
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Fetch a table containing the harrier league results |
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get_results_home()
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Get the URL of a single fixture |
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hmc()
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Hamiltonian Monte Carlo |
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hmc_da()
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Hamiltonian Monte Carlo |
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hmc_da_helper()
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Hamiltonian Monte Carlo |
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hmc_helper()
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Hamiltonian Monte Carlo |
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hmc_leapfrog_step()
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Leapfrog Step |
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hmc_leapfrogs()
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Perform n_steps Leapfrog steps |
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hmc_log_acceptance()
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Log Acceptance for the HMC algorithm |
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hmc_step()
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HMC Step |
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hmm_backward()
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hmm_backward_step()
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hmm_forward()
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Forward Filtering an HMM |
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hmm_forward_backward()
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Perform smoothing using the forward-backward algorithm |
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hmm_forward_step()
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Forward step for HMM |
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hmm_log_likelihood()
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Marginal log-likelihood HMM |
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hmm_simulate()
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Simulate from a hidden Markov model |
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latex_summary_table()
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latex_table_sim()
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lift_function()
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Lift a function to operate on bare numbers |
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ll_step()
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longest_batch()
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matching_course()
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metropolis()
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Metropolis Algorithm |
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metropolis_helper()
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Metropolis Helper |
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metropolis_step()
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Metropolis Step |
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minus()
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mvrnorm_prec()
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normalise()
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Normalise such that the values of the vector sum to one |
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not_all_na()
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Check if some columns contain non-missing values |
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parse_results_table()
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Get the raw HTML table from HTML |
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plot_diagnostics()
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plot_diagnostics_sim()
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Plot MCMC diagnostics with known values |
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plot_pdf()
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Plot a probability density function |
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plus()
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prior_posterior()
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Plot the prior and posterior |
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rename_clean()
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sample_beta()
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Sample beta |
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spatial_dlm()
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spatial_dlm_parallel()
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Gibbs sample spatial DLM in parallel |
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summary_table()
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thin()
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Thin MCMC |
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times()
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traceplot()
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Plot a traceplot |
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update_step_size()
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variable()
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Build a variable |