最小二乘法處理自變量誤差實(shí)驗(yàn)數(shù)據(jù)的方法

最小二乘法處理自變量誤差實(shí)驗(yàn)數(shù)據(jù)的方法
代錦輝成都理工大學(xué),成都610059摘　要:最小二乘法是處理實(shí)驗(yàn)數(shù)據(jù)的常用方法，一元線性回歸方程要求自變量無(wú)誤差或其誤差遠(yuǎn)小于因變量的誤差．但在實(shí)際的測(cè)量中，測(cè)量數(shù)據(jù)不可避免地會(huì)帶來(lái)誤差，該文在分析和總結(jié)了自變量有誤差的情況下，用最小二乘法處理實(shí)驗(yàn)數(shù)據(jù)時(shí)的幾種方法．[著者文摘]

關(guān)鍵詞:最小二乘法 誤差 自變量 不確定度
分類(lèi)號(hào):　O4-33[著者標(biāo)引]文獻(xiàn)標(biāo)識(shí)碼：文章編號(hào)：1672-4550（2006）04-0021-02欄目信息：實(shí)驗(yàn)技術(shù)
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Least Square Method to Process Data When the Independent Variable Has ErrorDAI Jin-hui Chengdu University of Technology Chengdu 610059Abstract:The least square method is experiment data. The regression equation requires the independent variable to have no error. But there is always error in measuring. When the independent variable has error-several methods to process data by least square method are discussed in this paper.[著者文摘]

Key words:least square method ; uncertainty ; independent variable; error