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.

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