tcasub: Subsetting features from a TCA model
In TCA: Tensor Composition Analysis

Description Usage Arguments Details Value Examples

View source: R/TCA.R

Extracts from a fitted TCA model (i.e. a value returned by the function tca) a subset of the features.

1	tcasub(tca.mdl, features, log_file = "TCA.log", debug = FALSE, verbose = TRUE)

`tca.mdl`	The value returned by applying the function `tca` to some data matrix`X`.
`features`	A vector with the identifiers of the features to extract (as they appear in the rows of `X`).
`log_file`	A path to an output log file. Note that if the file `log_file` already exists then logs will be appended to the end of the file. Set `log_file` to `NULL` to prevent output from being saved into a file; note that if `verbose == FALSE` then no output file will be generated regardless of the value of `log_file`.
`debug`	A logical value indicating whether to set the logger to a more detailed debug level; set `debug` to `TRUE` before reporting issues.
`verbose`	A logical value indicating whether to print logs.

This function allows to extract a subset of the features from a fitted TCA model (i.e. from a value returned by the function tca). This allows, for example, to extract and then perform post-hoc tests on only a small set of candidate features (e.g., using the function tcareg), without the need to run tca again for fitting the model to the candidate features.

A list with the estimated parameters of the model for the given set of features.

`W`	Equals to `tca.mdl$W`
`mus_hat`	A `q` by `k` matrix which is a subset of the matrix `tca.mdl$mus_hat`, where `q` is the number of features in the argument `features`.
`sigmas_hat`	A `q` by `k` matrix which is a subset of the matrix `tca.mdl$sigmas_hat`, where `q` is the number of features in the argument `features`.
`tau_hat`	Equals to `tca.mdl$tau_hat`
`gammas_hat`	A `q` by `k*p1` matrix which is a subset of the matrix `tca.mdl$gammas_hat`, where `q` is the number of features in the argument `features`.
`deltas_hat`	A `q` by `p2` matrix which is a subset of the matrix `tca.mdl$deltas_hat`, where `q` is the number of features in the argument `features`.
`gammas_hat_pvals`	A `q` by `k*p1` matrix which is a subset of the matrix `tca.mdl$gammas_hat_pvals`, where `q` is the number of features in the argument `features`. Note that if `tca.mdl$gammas_hat_pvals == NULL` then `gammas_hat_pvals` is also set to NULL.
`gammas_hat_pvals.joint`	A `q` by `p1` matrix which is a subset of the matrix `tca.mdl$gammas_hat_pvals.joint`, where `q` is the number of features in the argument `features`. Note that if `tca.mdl$gammas_hat_pvals.joint == NULL` then `gammas_hat_pvals` is also set to NULL.
`deltas_hat_pvals`	A `q` by `p2` matrix which is a subset of the matrix `tca.mdl$deltas_hat_pvals`, where `q` is the number of features in the argument `features`. Note that if `tca.mdl$deltas_hat_pvals == NULL` then `deltas_hat_pvals` is also set to NULL.

data <- test_data(50, 20, 3, 0, 0, 0.01)
tca.mdl <- tca(X = data$X, W = data$W)
tca.mdl.subset <- tcasub(tca.mdl, rownames(data$X)[1:10])
y <- matrix(rexp(50, rate=.1), ncol=1)
rownames(y) <- rownames(data$W)
# run tcareg test with an outcome y:
res <- tcareg(data$X[1:10,], tca.mdl.subset, y, test = "joint")