df.residual.fRegress: Degrees of Freedom for Residuals from a Functional Regression

View source: R/df.residual.fRegress.R

df.residual.fRegressR Documentation

Degrees of Freedom for Residuals from a Functional Regression


Effective degrees of freedom for residuals, being the trace of the idempotent hat matrix transforming observations into residuals from the fit.


## S3 method for class 'fRegress'
df.residual(object, ...)



Object of class inheriting from fRegress


additional arguments for other methods


1. Determine N = number of observations

2. df.model <- object\$df

3. df.residual <- (N - df.model)

4. Add attributes


The numeric value of the residual degrees-of-freedom extracted from object with the following attributes:


number of observations


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.


Spencer Graves


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.

See Also

fRegress df.residual

fda documentation built on April 27, 2022, 1:07 a.m.