hanaml.WhiteNoiseTest.Rd
hanaml.WhiteNoiseTest is a R wrapper for SAP HANA PAL white noise test.
hanaml.WhiteNoiseTest(
data,
key = NULL,
endog = NULL,
lag = NULL,
probability = NULL,
thread.ratio = NULL,
model.df = NULL
)
DataFrame
DataFrame containting the data.
character, optional
Name of the ID column.
Defaults to the first column if not provided.
character, optional
The endogenous variable, i.e. time series.
Defaults to the first non-ID column.
integer, optional
Specifies the lag autocorrelation coefficient that the statistic will be based on.
It corresponds to the degree of freedom of chi-square distribution.
Defaults to half of the sample size (n/2).
double, optional
The confidence level used for chi-square distribution.
The value is 1 - a, where a is the significance level.
Defaults to 0.9.
double, optional
Controls the proportion of available threads that can be used by this
function.
The value range is from 0 to 1, where 0 indicates a single thread,
and 1 indicates all available threads. Values between 0 and 1 will use up to
that percentage of available threads.
Values outside the range from 0 to 1 are ignored, and the actual number of threads
used is then be heuristically determined.
Defaults to -1.
integer, optional
Specifies the degrees of freedom occuppied by a model.
Should be provided if the input time-series data is the residual of some
raw time-series after being fitted by a time-series(e.g. ARIMA) model.
Defaults to 0.
DataFrame
Result of the forecast accuracy measurement, structured as follows:
STAT_NAME
: name of the accuracy measures.
STAT_VALUE
: values of the accuracy measures
WN: 1 for white noise, 0 for not white noise.
Q: Q statistics defined as above.
chi^2: chi-square distribution.
hanaml.WhiteNoiseTest is used to identify whether a time series is a white noise series. If white noise exists in the raw time series, the algorithm returns the value of 1. If not, the value of 0 will be returned.
Input DataFrame data:
> data$head(3)$Collect()
TIMESTAMP Y
1 0 1356
2 1 826
3 2 1586.00
Invoke the function:
> wn <- hanaml.WhiteNoiseTest(data,
key = "TIMESTAMP",
endog = "Y",
lag = 3,
model.df = 1,
probability = 0.9,
thread.ratio = 0.2)
Output:
> wn$Collect()
STAT_NAME STAT_VALUE
1 WN 0.000000
2 Q 5.576053
3 chi^2 4.605170