Sentences with phrase «squares regression which»

Not exact matches

They compare quantile regression results to those from a conventional Ordinary Least Squares (OLS) model (which focuses on distribution averages).

Basically, the optimal fingerprint techniques involved linear least - squares regression, which is familiar to many analysts.

There are little adjustments in the last few years, but in percentage terms the adjustments prior to 1961 are huge, and drop the R - squared of the regression from 90 % to 86 %, which also is huge.

We show four relevant empirical facts: i) the striking ability of the logarithmic averaged earning over price ratio to predict returns of the index, with an R squared which increases with the time horizon, ii) how this evidence increases switching from returns to gross returns, iii) moving over different time horizons, the regression coefficients are constant in a statistically robust way, and iv) the poorness of the prediction when the precursor is adjusted with long term interest rate.

5) Lindzen et al. reports a number of linear regressions, but does not report the r - square values, which give the percentage of total variation explained by the linear regression equation.

He's performing a linear least - squares regression, which only knows the two end - points and draws the best - fit straight line between the two.

A regression - based forecast for September ice extent around Svalbard (an area extending from 72 — 85N and 0 — 40E), which uses May sea surface temperatures, the March index of the Arctic Oscillation, and April ice conditions as predictors, yielded a mean ice extent in September 2010 of 255,788 square kilometers around Svalbard.

It should be noted simple linear regression using ordinary least squares is not really the best method for assessing these data as it depends on assumptions which are violated by global temperature measurements.

He explained that the warming rate was correctly calculated on the basis of the least - squares linear - regression trend, giving 0.39 degrees, which he had rounded for convenience.

This may be totally off, since I know squat about climate science & the high - powered statistical programs used, but when there is a dearth of data in the social sciences (not enough to give low enough p values on correlations & regressions, simply due to small numbers of data, which is sometimes due to loading in too many control variables), we sometimes turn to chi - square & log - linear analysis to see if actual data reveal patterns incongruent with expected patterns.

But it's important to note that potential tenants do not decide on which property they are going to rent by plugging the amenities and specs into a spreadsheet and running a logarithmic, covariate algorithm that takes the least - squares regression of the hypotenuse to determine the best value.