hanaml.BrownExponentialSmoothing {hana.ml.r} | R Documentation |
BrownExponentialSmoothing
Description
hanaml.BrownExponentialSmoothing is a R wrapper
for PAL Brown Exponential Smoothing algorithm.
Usage
hanaml.BrownExponentialSmoothing (conn.context,
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
conn.context |
ConnectionContext
The connection to the SAP HANA system.
|
data |
DataFrame
DataFrame containing the data.
|
key |
character, optional
Name of the ID column.
Defaults to the first column.
|
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 measure name.
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.
|
Details
The brown exponential smoothing model is suitable to model the time series
with trend but without seasonality.
In PAL, both non-adaptive and adaptive brown linear exponential smoothing are provided.
Value
Return a list of two DataFrame:
Examples
## Not run:
Input DataFrame data:
> data$Collect()
ID RAWDATA
1 1 143
2 2 152
3 3 161
4 4 139
......
20 20 227
21 21 223
22 22 242
23 23 239
24 24 266
besm <- hanaml.BrownExponentialSmoothing(conn.context = conn,
data = data,
alpha=0.1,
forecast.num=6,
adaptive.method=FALSE,
accuracy.measure='mse',
expost.flag=TRUE)
Output:
> besm[[2]]$Collect()
STAT_NAME STAT_VALUE
1 MSE 474.142
## End(Not run)
[Package
hana.ml.r version 1.0.8
Index]