Change data.frame values

Background

Distinguish between model values and predicted values.

Problem

Consider the following code:

library( 'gam' )

slope = 0.55
amplitude = 0.22
frequency = 3
noise = 0.75
x <- 1:200
y <- (slope * x / 100) + (amplitude * sin( frequency * x / 100 ))
ynoise <- y + (noise * runif( length( x ) ))

gam.object <- gam( ynoise ~ s( x ) )
p <- predict( gam.object, data.frame( x = 1:210 ) )

df <- data.frame( value=p, model='y' )

Question

What is the R syntax to set some model rows of the data frame (df) to 'n'?:

df[201:210,2] <- 'n'

Doesn't work, nor do any of the variations I have tried.

Related

http://stat.ethz.ch/R-manual/R-patched/library/base/html/Extract.data.frame.html

Thank you!

When you create the data frame, set the type of variable for the model to character rather than the default, which is factor. This can be done when you make the data frame.

df <- data.frame( value=p, model='y',  stringsAsFactors=FALSE)

Then you can assign any character value to the model variable in the data frame.

R> df[201:210,2] <- 'n'
R> table(df[,2])
  n   y 
 10 200 

The column is a factor:

R> sapply(df, class)
    value     model 
"numeric"  "factor" 
R> 

and has only one level:

R> table(df[,2])

  y 
200 

You probably need to re-level this to allow for 'n'.

Edit: Revisiting this now. Your gam() model does not use this second column, so what is wrong with simply doing

R> predict(gam.object, data.frame(x=201:210))
    1     2     3     4     5     6     7     8     9    10 
1.370 1.379 1.388 1.397 1.406 1.415 1.424 1.433 1.442 1.450 
R> 

In other words, you need neither the y nor the n but maybe I am misunderstanding something here. If so, could you please amend your question and make it clearer?