| 69 | 69 | #' biomarkerTMLEout <- biomarkertmle( |
|
| 70 | 70 | #' se = illuminaData[1:2, ], |
|
| 71 | 71 | #' varInt = benz_idx, |
|
| 72 | - | #' parallel = FALSE, |
|
| 72 | + | #' bppar_type = BiocParallel::SerialParam(), |
|
| 73 | 73 | #' g_lib = c("SL.mean", "SL.glm"), |
|
| 74 | 74 | #' Q_lib = c("SL.bayesglm", "SL.glm") |
|
| 75 | 75 | #' ) |
| 137 | 137 | } |
|
| 138 | 138 | ||
| 139 | 139 | # coerce matrix of baseline covariates to numeric |
|
| 140 | - | if (!all(apply(W, 2, class) == "numeric")) { |
|
| 140 | + | if (!all(is.numeric(apply(W, 2, class)))) { |
|
| 141 | 141 | W <- tibble::as_tibble(apply(W, 2, as.numeric)) |
|
| 142 | 142 | } |
|
| 143 | 143 |
| Files | Coverage |
|---|---|
| R | 77.50% |
| Project Totals (4 files) | 77.50% |
| 1 |
comment: false |
nhejazi
