SAP HANA Predictive Analysis Library (PAL)

CREATE column table PAL_FNLR_PDATA_TBL("POSITION" INT, "SCHEMA_NAME"
NVARCHAR(256), "TYPE_NAME" NVARCHAR(256), "PARAMETER_TYPE" VARCHAR(7));
INSERT INTO PAL_FNLR_PDATA_TBL values (1,'DM_PAL','PAL_FNLR_PREDICT_T','IN');
INSERT INTO PAL_FNLR_PDATA_TBL values (2,'DM_PAL','PAL_FNLR_COEFFICIENT_T','IN');
INSERT INTO PAL_FNLR_PDATA_TBL values (3,'DM_PAL','PAL_CONTROL_T','IN');
INSERT INTO PAL_FNLR_PDATA_TBL values (4,'DM_PAL','PAL_FNLR_FITTED_T','OUT');
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_DROP('DM_PAL','PAL_FORECAST_LNR_PROC');
CALL
SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE('AFLPAL','FORECASTWITHLNR','DM_PAL','PAL_FOR
ECAST_LNR_PROC',PAL_FNLR_PDATA_TBL);
DROP TABLE #PAL_CONTROL_TBL;
CREATE LOCAL TEMPORARY COLUMN TABLE #PAL_CONTROL_TBL ("Name" VARCHAR(100),
"INTARGS" INT, "DOUBLEARGS" DOUBLE,"STRINGARGS" VARCHAR(100));
INSERT INTO #PAL_CONTROL_TBL VALUES ('THREAD_NUMBER',8,null,null);
DROP TABLE PAL_FNLR_PREDICTDATA_TBL;
CREATE COLUMN TABLE PAL_FNLR_PREDICTDATA_TBL ( "ID" INT,"X1" DOUBLE);
INSERT INTO PAL_FNLR_PREDICTDATA_TBL VALUES (0,1);
INSERT INTO PAL_FNLR_PREDICTDATA_TBL VALUES (1,2);
INSERT INTO PAL_FNLR_PREDICTDATA_TBL VALUES (2,3);
INSERT INTO PAL_FNLR_PREDICTDATA_TBL VALUES (3,4);
INSERT INTO PAL_FNLR_PREDICTDATA_TBL VALUES (4,5);
INSERT INTO PAL_FNLR_PREDICTDATA_TBL VALUES (5,6);
INSERT INTO PAL_FNLR_PREDICTDATA_TBL VALUES (6,7);
DROP TABLE PAL_FNLR_COEFFICIENT_TBL;
CREATE COLUMN TABLE PAL_FNLR_COEFFICIENT_TBL ("ID" INT,"Ai" DOUBLE);
INSERT INTO PAL_FNLR_COEFFICIENT_TBL VALUES (0,14.86160299);
INSERT INTO PAL_FNLR_COEFFICIENT_TBL VALUES (1,98.29359746);
DROP TABLE PAL_FNLR_FITTED_TBL;
CREATE COLUMN TABLE PAL_FNLR_FITTED_TBL ("ID" INT,"Fitted" DOUBLE);
CALL DM_PAL.PAL_FORECAST_LNR_PROC(PAL_FNLR_PREDICTDATA_TBL,
PAL_FNLR_COEFFICIENT_TBL, "#PAL_CONTROL_TBL", PAL_FNLR_FITTED_TBL) with overview;
SELECT * FROM PAL_FNLR_FITTED_TBL;
Expected Result
PAL_FNLR_FITTED_TBL:
3.3.3 Exponential Regression
Exponential regression is an approach to modeling the relationship between a scalar variable y and one or
more variables denoted X. In exponential regression, data is modeled using exponential functions, and
unknown model parameters are estimated from the data. Such models are called exponential models.
In PAL, the implementation of exponential regression is to transform to linear regression and solve it:
y = β0 × exp(β1 × x1 + β2 × x2 + … + βn × xn)
256 P U B L I C
SAP HANA Predictive Analysis Library (PAL)
PAL Functions