hanaml.BrownExponentialSmoothing is a R wrapper for SAP HANA PAL Brown Exponential Smoothing algorithm.

hanaml.BrownExponentialSmoothing(
  data,
  key = NULL,
  endog = NULL,
  alpha = NULL,
  delta = NULL,
  forecast.num = NULL,
  adaptive.method = NULL,
  accuracy.measure = NULL,
  ignore.zero = NULL,
  expost.flag = NULL
)

Arguments

data

DataFrame
DataFrame containting the data.

key

character, optional
Name of the ID column.
Defaults to the first column if not provided.

endog

character, optional
The endogenous variable, i.e. time series.
Defaults to the first non-ID column.

alpha

double, optional
The smoothing constant alpha for brown exponential smoothing or the initialization value for adaptive brown exponential smoothing (0 < alpha < 1).

  • Defaults to 0.1 when Brown exponential smoothing

  • Defaults to 0.2 when Adaptive brown exponential smoothing

delta

double, optional
Value of weighted for At and Mt. Only valid when 'adaptive_method' is TRUE.
Defaults to 0.2

forecast.num

integer, optional
Number of values to be forecast.
Defaults to 0.

adaptive.method

logical, optional

  • FALSE: Brown exponential smoothing.

  • TRUE: Adaptive brown exponential smoothing.

Defaults to FALSE.

accuracy.measure

character or list of characters, optional
Specifies the method of accuracy evaluation.

  • mpe: Mean percentage error.

  • mse: Mean squared error.

  • rmse: Root mean squared error.

  • et: Error total.

  • mad: Mean absolute deviation.

  • mase: Out-of-sample mean absolute scaled error.

  • wmape: Weighted mean absolute percentage error.

  • smape: Symmetric mean absolute percentage error.

  • mape: Mean absolute percentage error.

No default value.

ignore.zero

logical, optional

  • FALSE: Uses zero values in the input dataset when calculating "mpe" or "mape".

  • TRUE: Ignores zero values in the input dataset when calculating "mpe" or "mape".

Only valid when accuracy.measure is "mpe" or "mape".
Defaults to FALSE.

expost.flag

logical, optional

  • FALSE: Does not output the expost forecast, and just outputs the forecast values.

  • TRUE: Outputs the expost forecast and the forecast values.

Defaults to TRUE.

Value

Return a list of two DataFrames:

  • DataFrame 1
    Forecast values.

  • DataFrame 2
    Statistics analysis content.

Details

The brown exponential smoothing model is suitable to model the time series with trend but without seasonality. In SAP HANA PAL, both non-adaptive and adaptive brown linear exponential smoothing are provided.

Examples

Input DataFrame data:


> data$Collect()
   ID RAWDATA
1   1     143
2   2     152
3   3     161
4   4     139
......
20 20     227
21 21     223
22 22     242
23 23     239
24 24     266

Call the function


> besm <- hanaml.BrownExponentialSmoothing(data = data,
                                           alpha=0.1,
                                           forecast.num=6,
                                           adaptive.method=FALSE,
                                           accuracy.measure="mse",
                                           expost.flag=TRUE)

Output:


> besm[[2]]$Collect()
  STAT_NAME    STAT_VALUE
1       MSE       474.142