SAP HANA Predictive Analysis Library (PAL)

3.3.2 Bi-Variate Natural Logarithmic Regression
Bi-variate natural logarithmic regression is an approach to modeling the relationship between a scalar variable
y and one variable denoted X. In natural logarithmic regression, data is modeled using natural logarithmic
functions, and unknown model parameters are estimated from the data. Such models are called natural
logarithmic models.
In PAL, the implementation of natural logarithmic regression is to transform to linear regression and solve it:
y = β1ln(x) + β0
Where β0 and β1 are parameters that need to be calculated.
Let x’ = ln(x)
Then y = β0 + β1 × x’
Thus, y and x’ is a linear relationship and can be solved with the linear regression method.
The implementation also supports calculating the F value and R^2 to determine statistical significance.
Prerequisites
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No missing or null data in the inputs.
The data is numeric, not categorical.
Given the structure as Y and X, there are more than 2 records available for analysis.
LNREGRESSION
This is a logarithmic regression function.
Procedure Generation
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE (‘AFLPAL’, ‘LNREGRESSION’,
‘’, '', );
The signature table should contain the following records:
Table 184:
Position Schema Name Table Type Name Parameter Type
1 IN
2 IN
3
4
OUT
OUT
SAP HANA Predictive Analysis Library (PAL)
PAL Functions P U B L I C 249