LG_boot_approx_scribe: Local Gaussian Approximations for bootstrap replicates,...

In LAJordanger/localgaussSpec: Local Gaussian Spectral Analysis

Local Gaussian Approximations for bootstrap replicates, scribe-function.

Description

This function takes care of the bookkeeping when the local Gaussian (auto- and cross-) correlations are computed for the lag-h pairs for bootstrapped replicates of a given time series.

Usage

LG_boot_approx_scribe(
  main_dir,
  data_dir,
  lag_max = NULL,
  LG_points = NULL,
  content_details = NULL,
  LG_type = NULL,
  .bws_mixture = NULL,
  bw_points = NULL,
  .bws_fixed = NULL,
  .bws_fixed_only = NULL,
  nb = NULL,
  boot_type = NULL,
  block_length = NULL,
  boot_seed = NULL,
  threshold = 500
)

Arguments

main_dir	The path to the main directory, that contains the file-hierarchy created when using the local Gassian approach for the investigation of time series.
data_dir	A specification of the directory to be used when loading and saving data.
lag_max	The number of lags to include in the analysis.
LG_points	An array that specifies the point at which it is desired to compute the local Gaussian estimates. The default value NULL will imply that the values used in the computations upon the original data are recycled. Values can alternatively be computed by the help of the function LG_select_points, but these must then be a subset of the original values.
content_details	A value from c("rho_only", "rho_log.fun", "rho_all"), which decides the amount of details stored from the local Gaussian approximations.
LG_type	One of c("par_five", "par_one"), i.e. should the Local Gaussian Autocorrelations be based on the approach using five parameters or the simplified approach using only one parameter. The default choice is "par_five".
.bws_mixture	An argument that specifies how the global bandwidths and those obtained by the nearest-neighbour strategy should be combined. The three available options are c("mixture", "local", "global"), which have the following effects. The alternatives local and global will respectively only select the nearest neighbour or global. These alternatives seems however to not work well when used on some parts of the lagged pairs of interest, i.e. the nearest neighbour values might be to "small" in the center of the distribution, whereas the global bandwidths seems to fail in the periphery of the distribution. The alternative mixture attempt to resolve this by (for each grid point) selecting the largest of the two alternative bandwidths. Note that the value of .bws_mixture decides how much information that is computed, i.e. the alternative local will turn off the computation of global bandwidths. However, the computations of the nearest neighbour bandwidths will also be computed when the alternative global is used, since it does not take long to compute and it is that function that creates the array we need as a mould for the result. If the user does not make a selection, then all three alternatives will be computed.
bw_points	A vector, default c(25, 35), that specifies the percentage of the observations that we want inside the "bandwidth-square". If .bws_mixture is selected to be global, then this argument will be ignored. and no nearest neighbours will be computed.
.bws_fixed	A vector of non-negative real values, that can be used to specify fixed values for the bandwidths (which might be of interest to do in a preliminary analysis). The default value NULL will prevent the computation of Local Gaussian Estimates based on fixed bandwidths.
.bws_fixed_only	A logic value, default FALSE, that can be used to drop the rather time-consuming data-driven estimation of bandwidths in favour of the simplified approach where fixed bandwidths are used instead. Note that .bws_fixed must be specified when .bws_fixed_only are set to TRUE.
nb	An integer that specifies how many bootstrap-replicates we want to use in our analysis. Default value 5 (at least in the development phase).
boot_type	This argument should be either "cibbb_tuples" or "block", the former gives an implementation of the circular index-based block bootstrap for tuples adjustment, whereas the latter gives the ordinary block bootstrap. The default option is "cibbb_tuples".
block_length	The length of the blocks to be used when boot_type="block" is used. Default value 20 in the development phase, but I suppose in general it should be some formula based on the time series under investigation.
boot_seed	Use this to enable reproducible results. The default value NULL will trigger a random seed to be selected for this value (that then will be recorded in case a reproduction of the result is desired later on).
threshold	An integer, default value 500 (measured in MB), that tells the program when a computation should be divided into smaller chunks. This reduces the chance of memory-related problems, but as the present incarnation of LG_splitter are rather stupid such problems might still occur for long time-series where a huge number of lags are included.

Details

This function records its arguments and compares them to a previously stored information-object for the time series under investigation, in order to avoid redoing previously performed computations. The function then calls LG_boot_approx when a new computation is required, the result is then saved to file, and the information-object is updated with the key details.

Note that default values are not given for any of the tuning parameters of the local Gaussian estimation algorithm. The basic idea is that such arguments only should be specified for the bootstrap-part if it is of interest to restrict the attention to a subset of the tuning parameters that were used for the local Gaussian investigation that was done on the original sample. When an argument is left unspecified, the bookkeeping-system will look up the value that was used during the investigation of the original sample, and that value will then be inherited to the present investigation.

Value

This function is a scribe that reads and records information, whereas another function performs the actual computation, see details for further information. A list containing the following key-information is always returned to the workflow.

done_before

Logical value that reveals if the computation has been performed before.

main_dir

The main_dir-argument is included here.

data_dir

The data_dir-argument is included here.

Note

Regarding the case where the LG_type-argument is equal to "par_one": The author of this package has always considered the "par_one"-approach to be reasonable when the aim of the investigation is to estimate a density at a given point. However, the extraction of the correlation value from the resulting density-estimate will in general not capture the local geometrical properties of the targeted distribution at the point of investigation. The "par_one"-approach is as such (in general) a complete waste of computation resources.

LAJordanger/localgaussSpec documentation built on May 6, 2023, 4:31 a.m.