hanaml.Correlation.Rd
hanaml.Correlation is a R wrapper for SAP HANA PAL correlation.
hanaml.Correlation(
data,
key,
cols = NULL,
thread.ratio = NULL,
method = NULL,
max.lag = NULL,
calculate.pacf = NULL,
calculate.confint = FALSE,
alpha = NULL,
bartlett = NULL
)
DataFrame
DataFrame containting the data.
character
Name of the ID column.
list of characters, optional
Specifies the columns in data
for correlation calculation.
If only one column is specified, then the auto-correlation of that column
will be calculated.
Defaults to the 1st non-ID column in data
.
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.
c("auto", "brute_force", "fft"), optional
Indicates the method to be used to calculate the correlation function.
Defaults to 'auto', i.e. automatically determined.
integer, optional
Maximum lag for the correlation function.
Defaults to sqrt(n), where n is the data number.
logical, optional
Controls whether to calculate PACF or not.
Valid only when only one series is provided.
Defaults to TRUE.
logical, optional
Controls whether to calculate confidence intervals or not.
If it is TRUE, two additional columns of confidence intervals are shown in the result.
Defaults to FALSE.
double, optional
Confidence bound for the given level are returned.
For instance if alpha=0.05, 95
Valid only when only calculate.confint is TRUE.
Defaults to 0.05.
logical, optional
- FALSE: using standard error to calculate the confidence bound.
- TRUE: using Bartlett's formula to calculate confidence bound.
Valid only when only calculate.confint is TRUE.
Defaults to TRUE.
DataFrame
LAG: ID column.
CV: ACV/CCV.
CF: ACF/CCF.
PACF: PACF. Null if cross-correlation is calculated.
Input DataFrame data:
> data$Collect()
TIMESTAMP Y
1 1 88
2 2 84
3 3 85
4 4 85
5 5 84
6 6 85
7 7 83
8 8 85
9 9 88
10 9 89
Invoke the function:
> cr <- hanaml.Correlation(data,
key = "TIMESTAMP",
cols = c("Y"),
thread.ratio = 0.4,
method = "auto",
calculate.pacf = TRUE)
Output:
> cr$Collect()
LAG CV CF PACF
1 0 3.640 1.00000000 1.0000000
2 1 0.924 0.25384615 0.2538462
3 2 -0.292 -0.08021978 -0.1546211
4 3 -0.628 -0.17252747 -0.1201993