R: Accuracy Measures

rmserr {pracma} | R Documentation

## Accuracy Measures

### Description

Calculates different accuracy measures, most prominently RMSE.

### Usage

    rmserr(x, y, summary = FALSE)

### Arguments

`x, y` | two vectors of real numbers
`summary` | logical; should a summary be printed to the screen?

### Details

Calculates six different measures of accuracy for two given vectors or sequences of real numbers:

MAE | Mean Absolute Error
MSE | Mean Squared Error
RMSE | Root Mean Squared Error
MAPE | Mean Absolute Percentage Error
LMSE | Normalized Mean Squared Error
rSTD | relative Standard Deviation

### Value

Returns a list with different accuracy measures.

### Note

Often used in Data Mining for predicting the accuracy of predictions.

### References

Gentle, J. E. (2009). Computational Statistics, section 10.3. Springer Science+Business Media LCC, New York.

### Examples

    x <- rep(1, 10)
    y <- rnorm(10, 1, 0.1)
    rmserr(x, y, summary = TRUE)

[Package pracma version 2.0.4 Index]