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Mechanism of Missing Data and Estimating them by Principal Components | ||
| IRAQI JOURNAL OF STATISTICAL SCIENCES | ||
| Article 28, Volume 10, Issue 1, 2010, Pages 227-238 PDF (0 K) | ||
| DOI: 10.33899/iqjoss.2010.029106 | ||
| Abstract | ||
| The mechanism of missing data requires knowing the reason behind missing them because different mechanism easy in which data is missed give rise to different specifications of the available sample. The data on which this study depends has been missed completely at random (MCAR) and changed into complete one. It can also be possible to find the magnitude of unbias after changing the data into complete one. Then observing the problem of multi linear variance which can be detected by Variance Inflation Factor (VIF) gauge. The estimation of data by the principal component, method follows that. Finally the study applies this data on the variants of oil products and the consumption of the refined products in certain regions in the world (1000 barrels a day from 1970 to 2004). | ||
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