Prepare parameters setup for DR-SC model fitting.
model_set_DRSC(
error_heter = TRUE,
wpca_int = FALSE,
int.model = "EEE",
approxPCA = FALSE,
beta_grid = seq(0.2, 4, by = 0.2),
coreNum = 5,
maxIter_ICM = 6,
maxIter = 25,
epsLogLik = 1e-05,
verbose = FALSE,
seed = 1
)a logical value, whether use the heterogenous error for DR-SC model, default as TRUE. If error.heter=FALSE, then the homogenuous error is used for probabilistic PCA model in DR-SC.
an optional logical value, means whether use the weighted PCA to obtain the initial values of loadings and other paramters, default as FALSE which means the ordinary PCA is used.
an optional string, specify which Gaussian mixture model is used in evaluting the initial values for DR-SC, default as "EEE"; and see Mclust for more models' names.
an optional logical value, whether use approximated PCA to speed up the computation for initial values.
a numeric vector, specify the smoothness parameter of Random Markov Field. The default is seq(0.2,4,0.2).
an integer value to decide how many cores are used to run in parallel.
the maximum iteration of ICM step, default as 6.
the maximum iteration of ICM-EM algorithm. The default is 25
an optional positive vlaue, tolerance vlaue of relative variation rate of the observed pseudo log-loglikelihood value, defualt as '1e-5'.
a logical value, whether output the information in iteration.
a postive integer, the random seed to be set.
model_set_DRSC(approxPCA=TRUE, coreNum=5)
#> $error_heter
#> [1] TRUE
#>
#> $wpca_int
#> [1] FALSE
#>
#> $int.model
#> [1] "EEE"
#>
#> $coreNum
#> [1] 5
#>
#> $approxPCA
#> [1] TRUE
#>
#> $beta_grid
#> [1] 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8
#> [20] 4.0
#>
#> $maxIter_ICM
#> [1] 6
#>
#> $maxIter
#> [1] 25
#>
#> $epsLogLik
#> [1] 1e-05
#>
#> $verbose
#> [1] FALSE
#>
#> $seed
#> [1] 1
#>