使用者:CYWVS/代理 (統計學)
In 統計學, a proxy or proxy variable is a 變數 that is not in itself directly relevant, but that serves in place of an unobservable or immeasurable variable.[1] In order for a variable to be a good proxy, it must have a close 相關, not necessarily linear, with the variable of interest. This correlation might be either positive or negative.
在統計學中，代理或代理變量是能夠替代一個潛在或不可測量的變量，但本身不與其直接相關的變量。[2]一個變量若需成為良好的代理，必須與關注的變量有緊密的相關性，但沒有必要是線性的。這種相關性可能是正相關，也可能是負相關。
Proxy variable must relate to an unobserved variable, must correlate with disturbance, and must not correlate with regressors once the disturbance is controlled for.
代理變量必須與潛在變量相關，
Examples
編輯In 社會科學s, proxy measurements are often required to stand in for variables that cannot be directly measured. This process of standing in is also known as 操作主義. Per-capita 國內生產總值 (GDP) is often used as a proxy for measures of 生活水平 or 生活質量. Montgomery et al. examine several proxies used, and point out limitations with each, stating "In poor countries, no single empirical measure can be expected to display all of the facets of the concept of income. Our judgment is that consumption per adult is the best measure among those collected in cross-sectional surveys."[3]
Likewise, country of origin or birthplace might be used as a proxy for 人種, or vice versa.
Frost lists several examples of proxy variables:[4] Widths of tree rings: proxy for historical environmental conditions; Per-capita GDP: proxy for quality of life; 身體質量指數 (BMI): proxy for true body fat percentage; years of education and/or GPA: proxy for cognitive ability; satellite images of ocean surface color: proxy for depth that light penetrates into the ocean over large areas; changes in height over a fixed time: proxy for hormone levels in blood.
See also
編輯References
編輯- ^ Upton, G., Cook,I. (2002) Oxford Dictionary of Statistics. OUP ISBN 978-0-19-954145-4
- ^ Upton, G., Cook,I. (2002) Oxford Dictionary of Statistics. OUP ISBN 978-0-19-954145-4
- ^ Mark R. Montgomery, Michele Gragnolati, Kathleen Burke, and Edmundo Paredes, Measuring Living Standards with Proxy Variables, Demography, Vol. 37 No. 2, pp. 155-174 (2000). (retrieved 9 Nov. 2015)
- ^ Jim Frost, Proxy Variables: The Good Twin of Confounding Variables, 22 September 2011 (retrieved 9 Nov. 2015)
- Toutenburg, Helge; Götz Trenkler. Proxy variables and mean square error dominance in linear regression. Journal of Quantitative Economics. 1992, 8: 433–442.
- Stahlecker, Peter; Götz Trenkler. Some further results on the use of proxy variables in prediction. The Review of Economics and Statistics (The MIT Press). 1993, 75 (4): 707–711. JSTOR 2110026. doi:10.2307/2110026.
- Trenkler, Götz; Peter Stahlecker. Dropping variables versus use of proxy variables in linear regression. Journal of Statistical Planning and Inference (NORTH-HOLLAND). 1996, 50 (1): 65–75. doi:10.1016/0378-3758(95)00045-3.
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