| elo.mse | R Documentation | 
Calculate the mean square error (Brier score) for a model.
mse(object, ..., subset = TRUE)
brier(object, ..., subset = TRUE)
## S3 method for class 'elo.run'
mse(object, ..., subset = TRUE)
## S3 method for class 'elo.glm'
mse(object, ..., subset = TRUE)
## S3 method for class 'elo.running'
mse(object, running = TRUE, discard.skipped = FALSE, ..., subset = TRUE)
## S3 method for class 'elo.markovchain'
mse(object, ..., subset = TRUE)
## S3 method for class 'elo.winpct'
mse(object, ..., subset = TRUE)
## S3 method for class 'elo.colley'
mse(object, ..., subset = TRUE)
| object | An object | 
| ... | Other arguments (not used at this time). | 
| subset | (optional) A vector of indices on which to calculate | 
| running | logical, denoting whether to use the running predicted values. | 
| discard.skipped | Logical, denoting whether to ignore the skipped observations in the calculation | 
Even though logistic regressions don't use the MSE on the y=0/1 scale, it can still be informative.
Note that the S3 method is mse.
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