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gets (version 0.40)

ISadditionalblocksearch: Internal function to carry out additional Block Search in isat: Leave-One-Out Block Search for Excessive Indicators

Description

Internal function that handles excessive indicator retention by re-running GETS on smaller blocks of indicators using a leave-one-out method. This can be necessary when following a block search, e.g. for IIS, more indicators than observations have been identified. Then another block search is carried out. This can be avoided by choosing tighter significance levels in t.pval or improving the specification.

Usage

ISadditionalblocksearch(mXis, isNames, y, y.n, mX, mXnames, mxkeep, 
  ISmatrixname, indicator.set, print.searchinfo, tol, LAPACK, userEstArg, 
  t.pval, gof.method, gofFunArg, max.regs, max.paths, arLjungB, archLjungB, 
  normality.JarqueB, user.diagnostics, include.gum, include.1cut, 
  include.empty, turbo, do.pet, ratio.threshold, max.block.size, 
  wald.pval, additional.block.search)

Value

A list containing:

ISfinalmodel

The final selected model.

estimations.counter

Updated estimation counter.

getsFun.counter

Updated function call counter.

ISblocks

Final block structure.

Arguments

mXis

Initial regressor matrix including previously selected indicators.

isNames

Character vector with names of the candidate indicator variables.

y

Response variable, typically a numeric vector or time-series.

y.n

Integer indicating the number of observations in the sample.

mX

Matrix of original regressors, excluding indicators.

mXnames

Character vector of column names corresponding to mX.

mxkeep

Indices of regressors to always retain during selection.

ISmatrixname

Character string naming the current IS matrix (e.g., "SIS", "TIS").

indicator.set

Matrix of candidate indicators from which subsets are selected.

print.searchinfo

Logical; if TRUE, outputs progress messages during execution.

tol

Numeric tolerance used in collinearity checks (see qr).

LAPACK

Logical; if TRUE, LAPACK is used for QR decomposition.

userEstArg

List specifying the user-defined estimation function and its arguments.

t.pval

Significance level for coefficient t-tests in the GETS algorithm.

gof.method

Character indicating whether to minimize or maximize the goodness-of-fit criterion.

gofFunArg

List containing the name and arguments of the GOF function used.

max.regs

Maximum number of regressions allowed per deletion path.

max.paths

Maximum number of GETS paths to be explored.

arLjungB

List with order and significance level for the Ljung-Box test on residual autocorrelation.

archLjungB

List with order and significance level for the Ljung-Box test on squared residuals (ARCH).

normality.JarqueB

Significance level for the Jarque-Bera test for normality; if NULL, test is skipped.

user.diagnostics

List containing user-specified diagnostic function and p-value thresholds.

include.gum

Logical; if TRUE, the General Unrestricted Model is included in terminal models.

include.1cut

Logical; if TRUE, the 1-cut model is included in terminal models.

include.empty

Logical; if TRUE, the empty model is included in terminal models.

turbo

Logical; avoids redundant GETS path evaluations if TRUE.

do.pet

Logical; if TRUE, performs Parsimonious Encompassing Tests (PETs).

ratio.threshold

Numeric ratio used to determine block sizes in relation to sample size.

max.block.size

Maximum number of indicators allowed per block during the leave-one-out search.

wald.pval

Significance threshold for Wald tests in the GETS algorithm.

additional.block.search

Default is FALSE. If isat() identifies (retains) too many indicators in the block search, a sensible model might not be estimable (e.g. due to a lack of available degrees of freedom). In this case, setting additional.block.search = TRUE carries out an additional block search using a Leave-one-Out method (e.g. for three blocks, indicators are assigned to block 1,2,3,1,2,3,1,2,3). This is an experimental feature.

Author

Moritz Schwarz, https://www.moritzschwarz.org/

See Also

ISMatricesLoop, isat