LG_approx_scribe: Local Gaussian Approximations, scribe-function

In LAJordanger/localgaussSpec: Local Gaussian Spectral Analysis

Local Gaussian Approximations, 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 a single time series. It can also digest a collection of samples from a parametric time series model.

Usage

LG_approx_scribe(
  main_dir,
  data_dir,
  TS,
  lag_max = ceiling(3 * sqrt(length(TS))),
  LG_points,
  .bws_mixture = c("mixture", "local", "global"),
  bw_points = c(25, 35),
  .bws_fixed = NULL,
  .bws_fixed_only = FALSE,
  content_details = c("rho_only", "rho_log.fun", "rho_all"),
  LG_type = c("par_five", "par_one")
)

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.
TS	The time series we want to investigate by means of techniques based on local Gaussian approximations. Note that this argument in the "wrapper"- and "scribe"-functions can be given as a character vector that specifies the file where TS from TS_LG_object was stored.
lag_max	The number of lags to include in the analysis. The default value ceiling(3*sqrt(length(TS))) will probably in most cases include more lags than actually required. It might thus be worthwhile to run some test and see if a smaller value can be used instead.
LG_points	An array that specifies the point at which it is desired to compute the local Gaussian estimates. Use the function LG_select_points to create this argument.
.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.
content_details	A character string from c("rho_only", "rho_log.fun", "rho_all"), of which the first will be selected if the user doesn't specify something else. The purpose of this argument is to decide the amount of details that should be stored from the estimates governed by the argument LG_type. The default rho_only is the one needed for the computation of the Local Gaussian Spectral Densities, whereas rho_log.fun in addition returns the estimated values of the logarithm of the density. The option rho_all will in addition return all the parameters when LG_type is given as par_five.
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".

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. This function calls LG_approx when a new computation is required, the result is then saved to file, and the information-object is updated with the key details.

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.