{eq}X_3 {/eq} = the rate of inflation (in percent) (quarterly model: N = 38) a. What does "least-squares estimates" mean? What is being estimated? What is being squared? In what sense are the squares "least"? b. What does it me...
The best linear predictor is a weighted average of the direct estimate and of the linear regression of the direct estimate onto the covariates. The weights depends on the reliability of the direct estimate and on the multiple correlation of the true score with the covariates. One application of...
The best linear predictor is a weighted average of the direct estimate and of the linear regression of the direct estimate onto the covariates. The weights depends on the reliability of the direct estimate and on the multiple correlation of the true score with the covariates. One application of...
Groundwater recharge is one of the most difficult components of the water balance to estimate as it is impossible to directly measure and must be inferred from other measurements. It is often recommended to use multiple methods when estimating recharge to acknowledge the inherent uncertainty in estim...
It appears that substitution rate estimates co-vary very strongly with their timescale of measurement; the shorter the timescale, the higher the estimated value. Foamy viruses have a long history of co-speciation with their hosts, and one of the lowest e
GP-Normal [16] which applies an input-dependent rescaling of the predicted variance (netcal.regression.GPNormal). Note: this method is also able to capture correlations between multiple input dimensions and can return a joint multivariate normal distribution as calibration output (cf. examples sectio...
the predicted range size has then been compared by calculating the mean squared deviation. To detect latitudinal trends in the improvement of SDMs after inclusion of either spatial, temporal, or spatio-temporal variability in SDMs, we calculated the mean and standard deviation of the difference ...
Gusma˜o et al and Leat et al.21–24 Problems of multicollinearity were evaluated on the full model (containing all explanatory variables), as collinear variables represent partial redundant information and correlations between variables generate unreliable individual estimates of regression coefficients....
A grid cell value cannot exceed one hail event per day even if multiple events were reported. This is to avoid double counting of the same event and to reduce the effects of varying population density on the gridded data set. The average annual large hail occurrences from the gridded ...
Given the vast uncertainty surrounding climate impacts, meta-analyses of global climate damage estimates are a key tool for determining the relationship be