exametrika (version 1.1.0)

Biclustering: Biclustering and Ranklustering

Description

performs biclustering, rankclustering, and their confirmatory models.

Usage

Biclustering(
  U,
  ncls = 2,
  nfld = 2,
  Z = NULL,
  w = NULL,
  na = NULL,
  method = "B",
  conf = NULL,
  mic = FALSE,
  maxiter = 100,
  verbose = TRUE
)

Value

nobs

Sample size. The number of rows in the dataset.

testlength

Length of the test. The number of items included in the test.

Nclass

number of classes you set

BRM

Bicluster Reference Matrix

FRP

Field Reference Profile

FRPIndex

Index of FFP includes the item location parameters B and Beta, the slope parameters A and Alpha, and the monotonicity indices C and Gamma.

TRP

Test Reference Profile

FMP

Field Membership Profile

Students

Class/Rank Membership Profile matrix.The s-th row vector of \(\hat{M}_R\), \(\hat{m}_R\), is the rank membership profile of Student s, namely the posterior probability distribution representing the student's belonging to the respective latent classes. It also includes the rank with the maximum estimated membership probability, as well as the rank-up odds and rank-down odds.

LRD

Latent Rank Distribution. see also plot.exametrika

LCD

Latent Class Distribution. see also plot.exametrika

LFD

Latent Field Distribution. see also plot.exametrika

RMD

Rank Membership Distribution.

TestFitIndices

Overall fit index for the test.See also TestFit

Arguments

U

U is either a data class of exametrika, or raw data. When raw data is given, it is converted to the exametrika class with the dataFormat function.

ncls

number of classes

nfld

number of fields

Z

Z is a missing indicator matrix of the type matrix or data.frame

w

w is item weight vector

na

na argument specifies the numbers or characters to be treated as missing values.

method

One of:

• "B": Biclustering

• "R": Ranklustering

conf

For the confirmatory parameter, you can input either a vector with items and corresponding fields in sequence, or a field membership profile matrix. In the case of the former, the field membership profile matrix will be generated internally. When providing a membership profile matrix, it needs to be either matrix or data.frame. The number of fields(nfld) will be overwrite to the number of columns of this matrix. The default is NULL, and the field membership matrix will be estimated according to the specified number of classes(ncls) and fields(nfld).

mic

Monotonic increasing IRP option. The default is FALSE.

maxiter

Maximum number of iterations. default is 100.

verbose

verbose output Flag. default is TRUE

Examples

# \donttest{
# Perform Biclustering with Binary method (B)
# Analyze data with 5 fields and 6 classes
Biclustering(J35S515, nfld = 5, ncls = 6, method = "B")

# Perform Biclustering with Rank method (R)
# Store results for further analysis and visualization
result.Ranklusteing <- Biclustering(J35S515, nfld = 5, ncls = 6, method = "R")

# Display the Bicluster Reference Matrix (BRM) as a heatmap
plot(result.Ranklusteing, type = "Array")

# Plot Field Reference Profiles (FRP) in a 2x3 grid
# Shows the probability patterns for each field
plot(result.Ranklusteing, type = "FRP", nc = 2, nr = 3)

# Plot Rank Membership Profiles (RMP) for students 1-9 in a 3x3 grid
# Shows the posterior probability distribution of rank membership for each student
plot(result.Ranklusteing, type = "RMP", students = 1:9, nc = 3, nr = 3)
# }