| df.residual.fRegress {fda} | R Documentation |
Degrees of Freedom for Residuals from a Functional Regression
Description
Effective degrees of freedom for residuals, being the trace of the
idempotent hat matrix transforming observations into residuals
from the fit.
Usage
## S3 method for class 'fRegress'
df.residual(object, ...)
Arguments
object |
Object of class inheriting from |
... |
additional arguments for other methods |
Details
1. Determine N = number of observations
2. df.model <- object$df
3. df.residual <- (N - df.model)
4. Add attributes
Value
The numeric value of the residual degrees-of-freedom extracted from
object with the following attributes:
nobs |
number of observations |
df.model |
effective degrees of freedom for the model, being the trace of the idempotent linear projection operator transforming the observations into their predictions per the model. This includes the intercept, so the 'degrees of freedom for the model' for many standard purposes that compare with a model with an estimated mean will be 1 less than this number. |
Author(s)
Spencer Graves
References
Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with R and Matlab, Springer, New York. Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York. Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York. Hastie, Trevor, Tibshirani, Robert, and Friedman, Jerome (2001) The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer, New York.