summary.robets: Summary robets model

In robets: Forecasting Time Series with Robust Exponential Smoothing

Description

Summary robets model

Usage

## S3 method for class 'robets'
summary(object, ...)

Arguments

object	An object of class robets.
...	Other undocumented arguments.

Value

A number of training set error measures: ME (mean error), RMSE (root mean squared error), MAE (mean absolute error), MPE (mean percentage error), MAPE (mean absolute percentage error), MedianE (median error), RTSE (root tau squared error), RTSPE (root tau squared percentage error).

Examples

model <- robets(nottem)
summary(model)

Example output

Registered S3 method overwritten by 'quantmod':
  method            from
  as.zoo.data.frame zoo 
ROBETS(M,A,M) 

Call:
 robets(y = nottem) 

  Smoothing parameters:
    alpha = 0.0185 
    beta  = 3e-04 
    gamma = 0.1859 

  Initial states:
    sigma = 0.4393 
    l = 49.2304 
    b = -0.0066 
    s=0.8513 0.8533 1.0199 1.112 1.1916 1.2446
           1.181 1.0997 0.9356 0.8762 0.81 0.8248

  sigma:  0.0522

  robAIC  robAICc   robBIC 
1706.429 1706.531 1716.871 
Training set: non robust error measures: 
       ME      RMSE       MAE       MPE      MAPE 
0.1639087 2.3913307 1.8691572 0.2950004 3.9774214 
Training set: robust error measures: 
   MedianE       RTSE      RTSPE 
 0.3684506  5.2575014 21.5644007 
        ME       RMSE        MAE        MPE       MAPE    MedianE       RTSE 
 0.1639087  2.3913307  1.8691572  0.2950004  3.9774214  0.3684506  5.2575014 
     RTSPE 
21.5644007 

robets documentation built on May 2, 2019, 6:51 a.m.