LinearRegression`
LinearRegression`

DesignedRegress

As of Version 7.0, DesignedRegress has been superseded by LinearModelFit.

DesignedRegress[matrix,vector]

finds a least–squares 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.

更多信息和选项

范例

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基本范例  (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:

Wolfram Research (2007)，DesignedRegress，Wolfram 语言函数，https://reference.wolfram.com/language/LinearRegression/ref/DesignedRegress.html.

文本

Wolfram Research (2007)，DesignedRegress，Wolfram 语言函数，https://reference.wolfram.com/language/LinearRegression/ref/DesignedRegress.html.

CMS

Wolfram 语言. 2007. "DesignedRegress." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/LinearRegression/ref/DesignedRegress.html.

APA

Wolfram 语言. (2007). DesignedRegress. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/LinearRegression/ref/DesignedRegress.html 年

BibTeX

@misc{reference.wolfram_2024_designedregress, author="Wolfram Research", title="{DesignedRegress}", year="2007", howpublished="\url{https://reference.wolfram.com/language/LinearRegression/ref/DesignedRegress.html}", note=[Accessed: 22-November-2024 ]}

BibLaTeX

@online{reference.wolfram_2024_designedregress, organization={Wolfram Research}, title={DesignedRegress}, year={2007}, url={https://reference.wolfram.com/language/LinearRegression/ref/DesignedRegress.html}, note=[Accessed: 22-November-2024 ]}