Least squares regression 

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memo179.pdf
... using the regression error terms i jt defined by the least squares regression model (2.9). then we have for all i j i 1 v2 i j t i jt 0 (2.21) compare with the first order condition for least squares ... regression equation (2.9) are positive, these restrictions might be violated by the least squares regression (section 2.2). hence we must minimise the sum of squares ...
cpb.nl

memo212.pdf
... for export reporting and import reporting. this model has been discussed, and estimated with least squares regression, by tsigas et al. (1992). unfortunately, they have not solved the fundamental problem ... ten cate (2007) two methods for the simultaneous estimation of the variances are presented least squares and maximum likelihood. the latter is numerically more complicated and less robust, but ...
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Microsoft Word - final version1..doc
... and to put speculators in a historical context. with the use of an ordinary least squares (ols) regression we will test to what extend the variable index speculators influences the price of arabica ... model. when we want to investigate effects over time we can use the ols (ordinary least squares) method because our dataset contains a temporal ordering. the ols method means that it minimizes ...
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