stepwise_search {autoRasch}

Stepwise Selection Search

Description

To search itemset that give maximum value of the criterion

Usage

stepwise_search(
  X,
  criterion = c("ipoqll", "ipoqlldif"),
  incl_set = c(),
  groups_map = c(),
  cores = NULL,
  isContinued = FALSE,
  prevData = c(),
  fileOutput = FALSE,
  tempFile = "temp_stepSearch.RData",
  isConvert = FALSE,
  setting_par_iq = c(),
  setting_par_oq = c(),
  method = c("fast", "novel"),
  isTraced = FALSE
)

backward_search(
  X,
  criterion = c("ipoqll", "ipoqlldif"),
  incl_set = c(),
  groups_map = c(),
  cores = NULL,
  isContinued = FALSE,
  prevData = c(),
  isConvert = FALSE,
  setting_par_iq = c(),
  fileOutput = FALSE,
  setting_par_oq = c(),
  method = c("fast", "novel"),
  tempFile = "temp_backSearch.RData",
  isTraced = FALSE
)

## S3 method for class 'search'
summary(object, ...)

## S3 method for class 'search'
print(x, ...)

plot_search(obj, remOrdered = TRUE, locateMax = TRUE, ...)

Arguments

X

A matrix or data.frame of the observed responses (ordinal or binary response).

criterion

The criterion that should be used. The default is ipoqll.

incl_set

A vector of initial items in the included set to start the search. The default is to start with full items.

groups_map

A matrix or vector to map the subject to the DIFs groups.

cores

An integer value of number of cores should be used for computation. The default is 2.

isContinued

A logical value whether this search is continuing another unfinished search.

prevData

The filename of the temporary .RData file of the unfinished search.

fileOutput

The filename if it is wished to save the output results in file (.RData and .csv) and FALSE if not.

tempFile

The filename of the temporary file to track the search progress. The default is "temp_stepSearch.RData" which also automatically produces "temp_stepSearch.csv".

isConvert

A logical value whether it is wanted to recompute the score of the search results using IPOQ-LL-DIF criterion.

setting_par_iq

a list of the optimization control setting parameters for the included set. See setting parameter in autoRaschOptions().

setting_par_oq

a list of the optimization control setting parameters for the included set. See setting parameter in autoRaschOptions().

method

The implementation option of log likelihood function. fast using a c++ implementation and novel using an R implementation.

isTraced

A logical value whether the progress need to be tracked or not.

object

The object of class 'search'.

...

Further arguments to be passed.

x

The object of class 'search'.

obj

An object of class "search".

remOrdered

A logical statement whether show the order of the items removal or not.

locateMax

A logical statement whether the location of the maximum score is needed to be marked or not.

Details

To search the itemset that give the maximum score.

Value

Matrix of the highest scores (IQ-LL, OQ-LL, and IPOQ-LL) for every number of items in the included set in the set along with the corresponding itemset.

Examples

## Not run: 
search_res <- backward_search(shortDIF,criterion = "ipoqll", incl_set = c(1:4), cores = 2)
plot_search(search_res, type="l")

## End(Not run)