Cumulative Distribution Function

hanaml.CDF is a R wrapper for SAP HANA PAL Cumulative Distribution Function

hanaml.CDF(data, distr.info, col = NULL, complementary = NULL)

Arguments

data	DataFrame DataFrame containting the data.
distr.info	list Specifies the probability distribution and its parameters. It should be specified by 3 parameters in the form of a list: list(distribution, distr.param1, distr.param2). distribution can be chosen from: {'uniform','normal', 'weibull', 'gamma'} . The distribution parameters should be chossen follow the following 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
col	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.
complementary	logical, optional By having complementary is TRUE, it calculates the CCDF value. Defaults to FALSE.

Value

• DataFrame
  return the cdf value of the distribution, evaluated at input data

  • INPUT_DATA: input data x

  • ROBABILITY: Probability

Details

This algorithm evaluates the Cumulative Distribution Function or complementary cumulative distribution function (CCDF) of a specified probability distribution evaluated at the values in x. CDF describes the value F(x) = P[X<=x] and CCDF the value F_c(x)=1-F(x)=P[X>x] where X is a real-valued random variable.

Examples

Input DataFrame data:

> data$$Collect()
  DATACOL
1    37.4
2   277.9
3   463.2

Call the function:

> result <- hanaml.CDF(data = data,
                       distr.info = list("weibull", 2.11995,277.698),
                       correction = FALSE)

Results:

> result$Collect()
  DATACOL PROBABILITY
1    37.4  0.01416002
2   277.9  0.63268765
3   463.2  0.94809354