hanaml.Quantile.Rd
hanaml.Quantile is a R wrapper for SAP HANA PAL Distribution Quantile.
hanaml.Quantile(data, distr.info, col = NULL, complementary = NULL)
DataFrame
DataFrame containting the cdf values.
list
choose the probability distribution and its parameters. :
Specifies the probability distribution and its parameters.
3 parameters should specify it in the form of a list:
list(distribution, distr.param1, distr.param2).
distribution can be choosen from:
{"uniform","normal", "weibull", "gamma"}
. The distribution parameters should be chosen follow the tabular:
Distribution | Parameter Name | Parameter Value | Constraints |
Uniform | "DistributionName" | "Uniform" | |
"Min" | "0.0" | Min < Max | |
"Max" | "1.0" | ||
Normal | "DistributionName" | "Normal" | |
"Mean" | "0.0" | ||
"Variance" | "1.0" | Variance > 0 | |
Weibull | "DistributionName" | "Weilbull" | |
"Shape " | "1.0" | Shape > 0 | |
"Scale" | "1.0" | Scale > 0 | |
Gamma | "DistributionName" | "Gamma" | |
"Shape " | "1.0" | Shape > 0 | |
"Scale" | "1.0" | Scale > 0 |
character, optional
Name of the data column that needs to be tested.
If it is not given, the input dataframe must only have one column.
logical, optional
By having complementary is TRUE, it calculates the CCDF value.
Defaults to FALSE.
DataFrame
Returns the cdf value of the distribution, evaluated at input data.
Structured as follow:
INPUT_DATA: input data
QUANTILE: quantile
This algorithm evaluates the value x where the CDF value p=F(x)=P[X<=x] or CCDF value p=F(x)=P[X>x] of a given probability density is reached, i.e. it evaluates F^-1(p).
Input DataFrame data:
> data$Collect()
DATACOL
1 0.300
2 0.500
3 0.632
4 0.800
Call the function:
> result <- hanaml.Quantile(data=data, list("weibull", 2.11995, 277.698), correction = FALSE)
Results:
> result$Collect()
INPUT_DATA QUANTILE
1 0.300 170.7559
2 0.500 233.6085
3 0.632 277.6551
4 0.800 347.5865