Package index • fsusieR

All functions

EBmvFR(): Empirical Bayes multivariate functional regression

EBmvFR.workhorse(): Empirical Bayes multivariate functional regression

HFT(): Perform Haar-Fisz tranform on count matrix

HMM_regression(): Compute refined estimate using HMM regression

TI_regression(): Compute refined estimate using translation invariant wavelet transform

affected_reg(): Extract coordinates of the regions affected by the different CS

bin_Y(): Binned reponsed data

change_fit(): Change postprocessing used in susiF object

colScale(): Scaling function from r-blogger

ebpm_normal(): Solve Gaussian approximation to Poisson mean problem

fsusie_log_plot(): fSuSiE Plots using Gviz

plot_susiF() plot(<susiF>) plot_susiF_pip() plot_susiF_effect(): fSuSiE Plots

get_fitted_effect(): Access fitted effect l

init_EBmvFR_obj(): Create an EBmvFR object

init_susiF_obj(): Initialize a susiF object using regression coefficients

pois_mean_GP(): Solve Gaussian approximation to Poisson mean problem

pois_mean_GP_opt_obj(): calculate objective function

pois_mean_GP_opt_obj_gradient(): calculate gradient vector

remap_data(): Ramp matrix of unevenly space data (or non power of two)

simu_IBSS_ash_vanilla(): Simulate data under a simple mixture normal prior

simu_IBSS_per_level(): Simulate data under the mixture normal prior

smash_regression(): Compute refined estimate using translation invariant wavelet transform

susiF(): Sum of Single Function

susiF.workhorse(): Sum of Single Function

univariate_functional_regression(): Wrapper for univariate functional regression used on susiF

vga_pois_solver(): Optimize vga poisson problem

vga_pois_solver_newton_1iter(): Optimize vga poisson problem 1 iteration.