remove unused level example bhistx

Author: davidruegamer

R/baselearnersX.R

@@ -409,8 +409,8 @@ X_histx <- function(mf, vary, args) {
 #' dataList$X1h <- I(X1h)   
 #' dataList$svals <- attr(data1, "xindex")
 #' ## add a factor variable 
-#' dataList$zlong <- factor(gl(n = 2, k = n/2, length = n*nygrid), levels = 1:3)  
-#' dataList$z <- factor(gl(n = 2, k = n/2, length = n), levels = 1:3)
+#' dataList$zlong <- factor(gl(n = 2, k = n/2, length = n*nygrid), levels = 1:2)  
+#' dataList$z <- factor(gl(n = 2, k = n/2, length = n), levels = 1:2)
 #'
 #' ## do the model fit with main effect of bhistx() and interaction of bhistx() and bolsc()
 #' mod <- FDboost(Y ~ 1 + bhistx(x = X1h, df = 5, knots = 5) + 

R/bootstrapCIs.R

@@ -148,7 +148,6 @@
 #' bootCIs <- bootstrapCI(m1, resampling_fun_inner = my_inner_fun,
 #'                        resampling_fun_outer = my_outer_fun,
 #'                        B_inner = 5, B_outer = 10) 
-# -> provide B_inner & B_outer only for enabling default plot
 #' }
 #' 
 #' ######## Example for scalar-on-function-regression with bsignal() 

R/crossvalidation.R

@@ -460,9 +460,10 @@ applyFolds <- function(object, folds = cv(rep(1, length(unique(object$id))), typ
         }
 
         # compute risk with integration weights like in FDboost::validateFDboost
-        risk <- sapply(grid, function(g){riskfct( response_oobweights, 
-                                                  withCallingHandlers(predict(mod[g], newdata = dat_oobweights, toFDboost = FALSE), warning = h2), 
-                                                  w = oobwstand )}) ## oobwstand[oobweights[object$id] != 0 ]
+        risk <- sapply(grid, function(g){riskfct( 
+          response_oobweights, 
+          withCallingHandlers(predict(mod[g], newdata = dat_oobweights, toFDboost = FALSE), warning = h2), 
+          w = oobwstand )}) ## oobwstand[oobweights[object$id] != 0 ]
 
       }else{
 
@@ -474,9 +475,10 @@ applyFolds <- function(object, folds = cv(rep(1, length(unique(object$id))), typ
         }
 
         # compute risk with integration weights like in FDboost::validateFDboost
-        risk <- sapply(grid, function(g){riskfct( response_oobweights, 
-                                                  withCallingHandlers(predict(mod[g], newdata = dat_oobweights, toFDboost = FALSE), warning = h2), 
-                                                  w = oobwstand[oobweights != 0 ])})
+        risk <- sapply(grid, function(g){riskfct( 
+          response_oobweights, 
+          withCallingHandlers(predict(mod[g], newdata = dat_oobweights, toFDboost = FALSE), warning = h2), 
+          w = oobwstand[oobweights != 0 ])})
 
       }