What Are Residual Degrees Of Freedom. The Residual degrees of freedom is the DF total minus the DF model 199 4 is 195. Similar lackoffit and replicate errors can be calculated as described in subsequent articles.
For example this could be a result of overdispersion where the variation is greater than predicted by the model. Second the residual deviance is relatively low which indicates that the log likelihood of our model is close to the log likelihood of the saturated model. The value of the residual degrees-of-freedom extracted from the object x.
If there are no replicates the lackoffit error is the same as the residual error.
So I have data like this - V2 V3 V4 V5 V6 V7 V8 2 270 413 29480 262 517 427 898 3 229 667 46440 30 457 418 1213 4 263 581 36650 30 508 385. This is a generic function which can be used to extract residual degrees-of-freedom for fitted models. The value of the residual degrees-of-freedom extracted from the object x. MS These are the Mean Squares the Sum of Squares divided by their respective DF.
