TD_​GOLDFELD_​QUANDT

The hope relative to the development of a univariate or multi-variate regression model is to create a regression model (estimator) that can be characterized as being BLUE: meaning the 'Best Linear Unbiased Estimator'. One of the properties of such an estimator is that the variance should be homoscedastic, meaning that the variance should be constant. The opposite behavior is that of a heteroscedastic variance

Options

ALGORITHM
Specifies the algorithm used for the regression.%%00010Permitted Values:%%00010 1. QR: QR decomposition is used for the regression.%%00010 2. PSI: pseudo-inverse based on singular value decomposition (SVD) is used to solve the regression.
FORMULA
Specifies the formula used in the regression operation. The name of the response variable must always be Y, and the name of the explanatory variable must always be X1. For example, 'Y = B0 + B1 * X1'.%%00010Notes:%%00010* The formula argument must be specified along with the 'algorithm' argument.%%00010* Use the following link to refer the formula rules:%%00010https://docs.teradata.com/r/Enterprise_IntelliFlex_VMware/Teradata-VantageTM-Unbounded-Array-Framework-Time-Series-Reference-17.20/Mathematic-Operators-and-Functions/Formula-Rules
OMIT
Positive real value > 0. Determines the number of of 'central sample values' to omit while forming the two 'test groups'. If less than 1.0, then the number of samples to be omitted is calculated as: OMIT * N; where N is total number of sample points. If greater than '1' then OMIT is interpreted as number of central points to omit.
ORIG_REGR_PARAMCNT
Positive Integer value > 0. A parameter indicating how many response and explanatory variables were present in the original regression, which is being analyzed by this test.
SIGNIFICANCE_LEVEL
The desired significance level for the test. 99%, aka, 0.01; 95%,aka,0.05
START_IDX
Optional parameter. Positive real value > 0. Identifies the split-point-index for the operation. If less than 1.0, then the split-point index is calculated as: START_IDX * N; where N is total number of sample points. If greater than '1' then START_IDX is interpreted as being the split-point index. If not present, than START_IDX is computed using integer math: START_IDX = (<total entries in series> - OMIT) / 2
Output Schema
Output Schema, if Volatile is true then use user login as the schema.
Output Table
Output Table
VAL Location
VAL Location
Volatile
Specifies whether the table should be a VOLATILE table. If true, then the table is automatically deleted, otherwise it is users responsibility to remove or clean it up for space.
TEST
Optional parameter. Has a value of: 'GREATER' or 'LESS' or 'TWOSIDED' ; DEFAULT (if not present) is 'GREATER'. Test value influences how GQ Test Statistic is computed and how Hypothesis is evaluated. See test description above to understand meaning of choosing a TEST value.
WEIGHTS
Optional Parameter. But when used must be accompanied by both a FORMULA and an ALGORITHM. FLAG having either a '0' or '1' value. A value of '1' means the last series found in the payload is to be interpreted as a series of weights that can be used to perform a weighted least squares regression solution.

Input Ports

Icon
Connection to a Teradata Database Instance
Icon
This function is executed against the original univariate or multivariate series

Output Ports

Icon
output of TD_GOLDFELD_QUANDT

Nodes

Extensions

Links

Download

To use this component in KNIME, download it from the below URL and open it in KNIME:

Download Component
On NodePit since: 2023-12-01
Last update: 2026-01-30
Created with KNIME version: v4.7.0

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!