BMSM | Bayesian Multi-scale Model for Smoothing Poisson sequence |
bmsm_control_default | Default control list of BMSM |
dwt.fn | Empirical Bayes wavelet smoothing for flashier |
ebbp_beta_mixture | Empirical Bayes for estimating Binomial probability |
ebnm_sgp | Sparse Gaussian process in EBNM syntax |
ebpm_pois_sgp | Poisson Sparse Gaussian Process |
ebps | empirical Bayes Poisson smoothing |
ebps_general_control_default | Default parameters for ebps |
ebps_init | init ebps |
ebps_init_control_default | Default parameters for ebps initialization |
ebps_smooth_control_default | Default parameters for ebps smoothing function |
ebps_twostep | Apply ebps then run smash as a two-step procedure |
GP | Define the empirical Bayes function |
grad_kernel_param | Get derivative of log kernel parameters and mean |
grad_post_mean | Gradient and hessian of eblo w.r.t post_mean |
hello | Hello, World! |
kernel | Define the squared exponential kernel |
Maternkernel | Matern Kernel |
neg_log_likelihood | Define the negative marginal log-likelihood |
Pois_GP | Fit Poisson + Gaussian process |
pois_reg_splitting | this function fits empirical Bayes Sparse Poisson regression |
pois_sgp | Sparse Gaussian process for Poisson data via variational... |
pois_sgp_elbo | calc elbo |
pois_sgp_get_posterior | Obtain full posterior distribution |
pois_sgp_matrix_helper | Helper function for matrix calculations |
pois_sgp_update_post_mean | Function for optimizing posterior mean |
pois_sgp_update_V | Function for updating posterior var |
pois_sgp_update_variational_param | Master function for optimizing variational parameters... |
pois_smooth_split | Smooth over-dispersed Poisson sequence via splitting method |
RBFkernel | RBF Kernel |
robust_smooth | empirical Bayes robust smoothing |
sgp | Fit Sparse Gaussian Process via variational inference |
smash_dwt | Empirical Bayes wavelet smoothing via DWT |
smash_gen_pois | Smooth Poisson sequence, accounting for nugget effect |
smash_two_step | A two step method for smoothing Poisson seq |
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