fit.ct3clus {simuclustfactor}

CT3Clus Model

Description

Implements simultaneous T3Clus and 3FKMeans integrating an alpha value between 0 and 1 inclusive for a weighted result.

Usage

fit.ct3clus(
  model,
  X_i_jk,
  full_tensor_shape,
  reduced_tensor_shape,
  alpha = 0.5
)

## S4 method for signature 'simultaneous'
fit.ct3clus(
  model,
  X_i_jk,
  full_tensor_shape,
  reduced_tensor_shape,
  alpha = 0.5
)

Arguments

model

Initialized simultaneous model.

X_i_jk

Matricized tensor along mode-1 (I objects).

full_tensor_shape

Dimensions of the tensor in full space.

reduced_tensor_shape

Dimensions of tensor in the reduced space.

alpha

0<alpha>1 hyper parameter. Model is T3Clus when alpha=1 and 3FKMeans when alpha=0.

Value

Output attributes accessible via the '@' operator.

• U_i_g0 - Initial object membership function matrix

• B_j_q0 - Initial factor/component matrix for the variables

• C_k_r0 - Initial factor/component matrix for the occasions

• U_i_g - Final/updated object membership function matrix

• B_j_q - Final/updated factor/component matrix for the variables

• C_k_r - Final/updated factor/component matrix for the occasions

• Y_g_qr - Derived centroids in the reduced space (data matrix)

• X_i_jk_scaled - Standardized dataset matrix

• BestTimeElapsed - Execution time for the best iterate

• BestLoop - Loop that obtained the best iterate

• BestIteration - Iteration yielding the best results

• Converged - Flag to check if algorithm converged for the K-means

• nConverges - Number of loops that converged for the K-means

• TSS_full - Total deviance in the full-space

• BSS_full - Between deviance in the reduced-space

• RSS_full - Residual deviance in the reduced-space

• PF_full - PseudoF in the full-space

• TSS_reduced - Total deviance in the reduced-space

• BSS_reduced - Between deviance in the reduced-space

• RSS_reduced - Residual deviance in the reduced-space

• PF_reduced - PseudoF in the reduced-space

• PF - Weighted PseudoF score

• Labels - Object cluster assignments

• Fs - Objective function values for the KM best iterate

• Enorm - Average l2 norm of the residual norm.

References

Tucker L (1966). “Some mathematical notes on three-mode factor analysis.” Psychometrika, 31(3), 279-311. doi:10.1007/BF02289464, https://ideas.repec.org/a/spr/psycho/v31y1966i3p279-311.html. Rocci R, Vichi M (2005). “Three-Mode Component Analysis with Crisp or Fuzzy Partition of Units.” Psychometrika, 70, 715-736. doi:10.1007/s11336-001-0926-z. Vichi M, Kiers HAL (2001). “Factorial k-means analysis for two-way data.” Computational Statistics and Data Analysis, 37(1), 49-64. https://EconPapers.repec.org/RePEc:eee:csdana:v:37:y:2001:i:1:p:49-64. Vichi M, Rocci R, Kiers H (2007). “Simultaneous Component and Clustering Models for Three-way Data: Within and Between Approaches.” Journal of Classification, 24, 71-98. doi:10.1007/s00357-007-0006-x.

See Also

fit.t3clus fit.3fkmeans simultaneous

Examples

X_i_jk = generate_dataset()$X_i_jk
model = simultaneous()
ct3clus = fit.ct3clus(model, X_i_jk, c(8,5,4), c(3,3,2), alpha=0.5)