B_h_bound               Compute weak white noise confidence bound for
                        autocorrelation coefficient.
B_iid_bound             Compute strong white noise confidence bound for
                        autocorrelation coefficient.
GOF_far                 Goodness-of-fit test for FAR(1)
Q_WS_hyp_test           Compute size alpha single-lag hypothesis test
                        under weak or strong white noise assumption
autocorrelation_coeff_h
                        'autocorrelation_coeff_h' Computes the
                        approximate functional autocorrelation
                        coefficient at a given lag.
autocorrelation_coeff_plot
                        Plot Confidence Bounds of Estimated Functional
                        Autocorrelation Coefficients
autocov_approx_h        Compute the approximate autocovariance at
                        specified lag
bartlett_kernel         Bartlett Kernel Function
block_bootsrap          'block_bootstrap' Performs a block bootstrap on
                        the functional data f_data with block size b.
brown_motion            'brown_motion' Creates at J x N matrix,
                        containing N independent Brownian motion sample
                        paths in each of the columns.
center                  Center functional data
covariance_diag_store   List storage of diagonal covariances.
covariance_i_j          Compute the approximate covariance tensor for
                        lag windows defined by i,j
covariance_i_j_vec      Compute the approximate covariance tensor for
                        lag windows defined by i,j
daniell_kernel          Daniell Kernel Function
diagonal_autocov_approx_0
                        Compute the diagonal covariance
diagonal_covariance_i   Compute the approximate diagonal covariance
                        matrix for lag windows defined by i
far_1_S                 'far_1_S' Simulates an FAR(1,S)-fGARCH(1,1)
                        process with N independent observations, each
                        observed discretely at J points on the interval
                        [0,1].
fgarch_1_1              'fgarch_1_1' Simulates an fGARCH(1,1) process
                        with N independent observations, each observed
fport_test              Compute Functional Hypothesis Tests
iid_covariance          Compute part of the covariance under a strong
                        white noise assumption
iid_covariance_vec      Compute part of the covariance under a strong
                        white noise assumption
independence_test       Independence Test
multi_lag_test          Multi-Lag Hypothesis Test
parzen_kernel           Parzen Kernel Function
scalar_covariance_i_j   Compute the approximate covariance at a point
                        for lag windows defined by i,j
scalar_covariance_i_j_vec
                        Compute the approximate covariance at a point
                        for lag windows defined by i,j
single_lag_test         Single-Lag Hypothesis Test
spectral_test           Spectral Density Test
