LinearRegression`
LinearRegression`

DesignedRegress

As of Version 7.0, DesignedRegress has been superseded by LinearModelFit.

DesignedRegress[matrix,vector]

finds a leastsquares fit given the design matrix matrix and response vector vector.

DesignedRegress[svd,vector]

finds a fit given the singular value decomposition svd of a design matrix.

Details

Examples

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Basic Examples  (1)

Linear regression with one constant and one nonconstant basis function:

Options  (5)

RegressionReport  (1)

Linear regression with a specific list of report values:

BasisNames  (1)

Linear regression with basis functions labeled b1 and b2:

Weights  (2)

Weighted regression with explicit weights for each data element:

Weighted regression with weights equal to the squares of the measured responses:

ConfidenceLevel  (1)

Linear regression with .99 confidence level for confidence intervals: