Handling of missing values

[hofnerb]

The handling of missing values in gamboost is seriously corrupted. Missing values in glmboost are not an issue. For an example to reproduce the issue see below:

### Simulate data with missing values and check if results are correct.
library("mvtnorm")
library("mboost")

set.seed(1234)
x <- rmvnorm(100, mean = rep(0, 10))
head(x)

beta <- c(1, 2, 3, -1, -2, -3, rep(0, 4))
y <- rnorm(100, mean = crossprod(t(x), beta))

## complete data
data <- as.data.frame(x)
names(data) <- paste0("x", 1:10)
data$y <- y
head(data)

## now data with missings
miss <- data
miss$x1[1:10] <- NA
miss$x3[11:20] <- NA

## complete cases from miss
cc <- miss[complete.cases(miss),]

#############################################
## fit glmboost models
#############################################

mod <- glmboost(y ~ ., data = data)
mstop(mod) <- 1000
coef(mod)
## ok

mod <- glmboost(y ~ ., data = miss)
mstop(mod) <- 1000
coef(mod)
## ok

mod <- glmboost(y ~ ., data = cc)
mstop(mod) <- 1000
coef(mod)
## ok

#############################################
## fit gamboost models
#############################################

mod <- gamboost(y ~ ., baselearner = bols, data = data)
mstop(mod) <- 1000
## extract coefficients (and drop intercept of each base-learner)
sapply(coef(mod), function(x) x[2])
## ok

fm <- as.formula(paste0("y ~ ", paste0(paste0("x", c(2, 4:10)), collapse = "+")))
mod <- gamboost(fm, baselearner = bols, data = miss)
sapply(coef(mod), function(x) x[2])
## ok

fm <- as.formula(paste0("y ~ ", paste0(paste0("x", c(1, 3)), collapse = "+")))
mod <- gamboost(fm, baselearner = bols, data = miss)
sapply(coef(mod), function(x) x[2])
## not ok!!

(This issue was reported by Max Schneider)

[hofnerb]

Also check the impact of na.action in glmboost as reported on stackoverflow.

I guess this is not a real issue.