hanaml.LRSeasonalAdjust {hana.ml.r}R Documentation

Linear Regression with Damped Trend and Seasonal Adjust

Description

hanaml.LRSeasonalAdjust is a R wrapper for PAL Linear regression with damped trend and seasonal adjust.

Usage

hanaml.LRSeasonalAdjust(conn.context,
                        data,
                        key,
                        endog= NULL,
                        forecast.length = NULL,
                        trend = NULL,
                        affect.future.only = NULL,
                        seasonality = NULL,
                        seasonal.period = NULL,
                        accuracy.measure = NULL,
                        seasonal.handle.method = NULL,
                        expost.flag = NULL,
                        ignore.zero = NULL)

Arguments

conn.context

ConnectionContext
Connection to SAP HANA System.

data

DataFrame
DataFrame containing the data.

key

character
Name of the ID column.

endog

character, optional
The endogenous variable of the given time series in data.
Defaults to the first non-ID column.

forecast.length

integer, optional
Length of the final forecast results.
Defaults to 1.

trend

double, optional
Damped trend factor. Value range is (0,1].
Defaults to 1.

affect.future.only

logical, optional
Specifies whether the damped trend affects the history.

  • FALSE: Affects all.

  • TRUE: Affects the future only.

Defaults to TRUE.

seasonality

integer, optional
Specifies whether the data represents seasonality.

  • 0: Non-seasonality.

  • 1: Seasonality exists and user inputs the value of periods.

  • 2: Automatically detects seasonality.

Defaults to 0.

seasonal.period

integer, optional
Length of seasonal period. seasonal.period is only valid when seasonality is 1.
If this parameter is not specified, the seasonality value will be changed from 1 to 2, that is, from user-defined to automatically-detected.
No default value.

accuracy.measure

character or list of character, optional
Specifies accuracy measure.The criterion used for the optimization.

  • 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.

seasonal.handle.method

character, optional
Method used for calculating the index value in the seasonal_period.

  • "average": Average method.

  • "lr": Fitting linear regression.

Defaults to 'average'.

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.

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'.

Defaults to FALSE.

Value

Returns a list of two DataFrame:

Examples

## Not run: 
Input data:
> data$Collect()
  TIMESTAMP         Y
1         1  5328.172
2         2  7701.608
3         3 11248.606
4         4  9478.945
5         5  6138.471
6         6  8829.956
7         7  2838.390
invoke the function:
> lr <- hanaml.LRSeasonalAdjust(conn,
                                data,
                                key = "TIMESTAMP",
                                endog = "Y",
                                forecast.length = 1,
                                trend = 0.9,
                                affect.future.only = TRUE,
                                seasonality = 2,
                                seasonal.handle.method = "lr",
                                accuracy.measure =  list("mape","mpe"),
                                expost.flag = TRUE,
                                ignore.zero = TRUE)
Ouput:
> lr[[1]]$Collect()
  TIMESTAMP    VALUE
1         1 8472.320
2         2 8103.649
3         3 7734.978
4         4 7366.307
5         5 6997.636
6         6 6628.965
7         7 6260.294
8         8 5928.490

> lr[[2]]$Collect()
   STAT_NAME   STAT_VALUE
1  Intercept 8840.9904286
2      Slope -368.6708929
3       MAPE    0.3960495
4        MPE   -0.1719060
5 HandleZero    0.0000000
 
## End(Not run)
[Package hana.ml.r version 1.0.8 Index]