R Under development (unstable) (2025-02-23 r87804 ucrt) -- "Unsuffered Consequences"
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> require("gamboostLSS")
Loading required package: gamboostLSS
Loading required package: mboost
Loading required package: parallel
Loading required package: stabs

Attaching package: 'gamboostLSS'

The following object is masked from 'package:stats':

    model.weights

> ### Data generating process:
> set.seed(1907)
> x1 <- rnorm(500)
> x2 <- rnorm(500)
> x3 <- rnorm(500)
> x4 <- rnorm(500)
> x5 <- rnorm(500)
> x6 <- rnorm(500)
> mu    <- exp(1.5 +1 * x1 +0.5 * x2 -0.5 * x3 -1 * x4)
> sigma <- exp(-0.4 * x3 -0.2 * x4 +0.2 * x5 +0.4 * x6)
> y <- numeric(500)
> for( i in 1:500)
+     y[i] <- rnbinom(1, size = sigma[i], mu = mu[i])
> dat <- data.frame(x1, x2, x3, x4, x5, x6, y)
> 
> model <- glmboostLSS(y ~ ., families = NBinomialLSS(), data = dat,
+                      control = boost_control(mstop = 10),
+                      center = TRUE, method = "cyclic")
> s1 <- stabsel(model, q = 5, PFER = 1, B = 10) ## warning is expected
Run stabsel ....................
Warning message:
In stabsel.mboostLSS(model, q = 5, PFER = 1, B = 10) :
  'mstop' too small in 11 of the 20 subsampling replicates to select 'q' base-learners; Increase 'mstop' bevor applying 'stabsel'
> plot(s1)
> plot(s1, type = "paths")
> 
> model <- glmboostLSS(y ~ ., families = NBinomialLSS(), data = dat,
+                      control = boost_control(mstop = 10),
+                      center = TRUE, method = "noncyclic")
> s2 <- stabsel(model, q = 5, PFER = 1, B = 10) ## warning is expected
Run stabsel ....................
Warning message:
In stabsel.mboostLSS(model, q = 5, PFER = 1, B = 10) :
  'mstop' too small in 20 of the 20 subsampling replicates to select 'q' base-learners; Increase 'mstop' bevor applying 'stabsel'
> plot(s2)
> plot(s2, type = "paths")
> 
> ## with informative sigma:
> sigma <- exp(-0.4 * x3 -0.2 * x4 +0.2 * x5 + 1 * x6)
> y <- numeric(500)
> for( i in 1:500)
+     y[i] <- rnbinom(1, size = sigma[i], mu = mu[i])
> dat <- data.frame(x1, x2, x3, x4, x5, x6, y)
> 
> model <- glmboostLSS(y ~ ., families = NBinomialLSS(), data = dat,
+                      control = boost_control(mstop = 10),
+                      center = TRUE, method = "cyclic")
> s3 <- stabsel(model, q = 5, PFER = 1, B = 10) ## warning is expected
Run stabsel ....................
Warning message:
In stabsel.mboostLSS(model, q = 5, PFER = 1, B = 10) :
  'mstop' too small in 18 of the 20 subsampling replicates to select 'q' base-learners; Increase 'mstop' bevor applying 'stabsel'
> plot(s3)
> plot(s3, type = "paths")
> 
> model <- glmboostLSS(y ~ ., families = NBinomialLSS(), data = dat,
+                      control = boost_control(mstop = 10),
+                      center = TRUE, method = "noncyclic")
> s4 <- stabsel(model, q = 5, PFER = 1, B = 10) ## warning is expected
Run stabsel ....................
Warning message:
In stabsel.mboostLSS(model, q = 5, PFER = 1, B = 10) :
  'mstop' too small in 20 of the 20 subsampling replicates to select 'q' base-learners; Increase 'mstop' bevor applying 'stabsel'
> plot(s4)
> plot(s4, type = "paths")
> 
> proc.time()
   user  system elapsed 
   4.59    0.32    4.92