SAP HANA Predictive Analysis Library (PAL)

The expected results are as follows:
The results show that the shape values for both treatments are greater than 1, indicating the failure rate
increases over time.
Step 3
Get the CDF (cumulative distribution function) of Weibull distribution for the linoleic acid treatment data:
SET SCHEMA DM_PAL;
DROP TYPE PAL_DISTRPROB_DATA_T;
CREATE TYPE PAL_DISTRPROB_DATA_T AS TABLE("DATACOL" DOUBLE);
DROP TYPE PAL_DISTRPROB_DISTRPARAM_T;
CREATE TYPE PAL_DISTRPROB_DISTRPARAM_T AS TABLE(
"NAME" VARCHAR(50),
"VALUE" VARCHAR(50)
);
DROP TYPE PAL_DISTRPROB_RESULT_T;
CREATE TYPE PAL_DISTRPROB_RESULT_T AS TABLE(
"INPUTDATA" DOUBLE,
"PROBABILITY" DOUBLE
);
DROP TYPE PAL_CONTROL_T;
CREATE TYPE PAL_CONTROL_T AS TABLE(
"NAME" VARCHAR (50),
"INTARGS" INTEGER,
"DOUBLEARGS" DOUBLE,
"STRINGARGS" VARCHAR (100)
);
DROP TABLE PAL_DISTRPROB_PDATA_TBL;
CREATE COLUMN TABLE PAL_DISTRPROB_PDATA_TBL(
"POSITION" INT,
"SCHEMA_NAME" NVARCHAR(256),
"TYPE_NAME" NVARCHAR(256),
"PARAMETER_TYPE" VARCHAR(7)
);
INSERT INTO PAL_DISTRPROB_PDATA_TBL VALUES (1, 'DM_PAL','PAL_DISTRPROB_DATA_T',
'IN');
INSERT INTO PAL_DISTRPROB_PDATA_TBL VALUES (2,'DM_PAL',
'PAL_DISTRPROB_DISTRPARAM_T', 'IN');
INSERT INTO PAL_DISTRPROB_PDATA_TBL VALUES (3, 'DM_PAL','PAL_CONTROL_T', 'IN');
INSERT INTO PAL_DISTRPROB_PDATA_TBL VALUES (4,
'DM_PAL','PAL_DISTRPROB_RESULT_T', 'OUT');
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_DROP('DM_PAL','PAL_DISTRPROB_PROC');
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE('AFLPAL',
'DISTRPROB','DM_PAL','PAL_DISTRPROB_PROC', PAL_DISTRPROB_PDATA_TBL);
DROP TABLE PAL_DISTRPROB_DATA_TBL;
CREATE COLUMN TABLE PAL_DISTRPROB_DATA_TBL LIKE PAL_DISTRPROB_DATA_T;
INSERT INTO PAL_DISTRPROB_DATA_TBL VALUES (6);
INSERT INTO PAL_DISTRPROB_DATA_TBL VALUES (8);
INSERT INTO PAL_DISTRPROB_DATA_TBL VALUES (12);
INSERT INTO PAL_DISTRPROB_DATA_TBL VALUES (20);
INSERT INTO PAL_DISTRPROB_DATA_TBL VALUES (24);
INSERT INTO PAL_DISTRPROB_DATA_TBL VALUES (30);
SAP HANA Predictive Analysis Library (PAL)
End-to-End Scenarios P U B L I C 573