SAP HANA Predictive Analysis Library (PAL)

"DOUBLEARGS" DOUBLE,
"STRINGARGS" VARCHAR (100)
);
INSERT INTO #PAL_CONTROL_TBL VALUES ('ALPHA', null, 0.2, null);
INSERT INTO #PAL_CONTROL_TBL VALUES ('METHOD', 2, null, null);
DROP TABLE PAL_GRUBBS_OUTLIERS_TBL;
CREATE COLUMN TABLE PAL_GRUBBS_OUTLIERS_TBL LIKE PAL_GRUBBS_OUTLIERS_T;
DROP TABLE PAL_GRUBBS_STATISTICS_TBL;
CREATE COLUMN TABLE PAL_GRUBBS_STATISTICS_TBL LIKE PAL_GRUBBS_STATISTICS_T;
CALL "DM_PAL".PAL_GRUBBS_PROC(PAL_GRUBBS_DATA_TBL, "#PAL_CONTROL_TBL",
PAL_GRUBBS_OUTLIERS_TBL, PAL_GRUBBS_STATISTICS_TBL) with overview;
SELECT * FROM PAL_GRUBBS_OUTLIERS_TBL;
SELECT * FROM PAL_GRUBBS_STATISTICS_TBL;
Expected Result
PAL_GRUBBS_OUTLIERS_TBL:
PAL_GRUBBS_STATISTICS_TBL:
3.7.6 Kaplan-Meier Survival Analysis
The Kaplan-Meier estimator is a non-parametric statistic used to estimate the survival function from lifetime
data. It is often used to measure the time-to-death of patients after treatment or time-to-failure of machine
parts.
Sometimes subjects under study are refused to remain in the study or some of the subjects may not
experience the event before the end of the study, or you lose touch with them midway in the study. These
situations are labeled as censored observations.
The Kaplan-Meier estimator of survival function is calculated as:
Where n i is the number of subjects at risk and d i is the number of subjects who fail, both at time t i .
518 P U B L I C
SAP HANA Predictive Analysis Library (PAL)
PAL Functions