Sentences with phrase «squares regression models»

A false colour composite of predicted abundance of Graminoids (Red) Shrubs (Green) and Bryophytes (Blue) representing vegetation composition on a peatland from Partial Least Squares Regression models on a hyperspectral image.

«Three beliefs about God were tested separately in ordinary least squares regression models to predict five classes of psychiatric symptoms: general anxiety, social anxiety, paranoia, obsession, and compulsion,» reads the abstract for this paper.

Not exact matches

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

He tests the model via a least squares regression of actual Bitcoin price on modeled price with adjustment for inflation due to new Bitcoin creation.

Modern Portfolio Theory concepts such as Alpha and Beta, Standard Deviation, the Sharpe ratio, Capital Asset Pricing Model (CAPM), Regression, and R - squared have provided a foundation for debate that has continued to provide additional insight into the relationship between investment risk and returns.

Regarding the emergent constraint used in Brient & Schneider (2016), it is noteworthy that if the models are weighted by reference to their consistency with the data, regression of ECS on TLC reflection variability explains almost none of the intermodel ECS variation — the R - squared is negligible.

I work with t tests, Chi square, Z scores, linear regression, multiple regression, multi level modeling, ANOVA, MANOVA, and other statistical techniques.

The ordinary least squares (OLS) regression approach used will, however, underestimate Y in the presence of fluctuations in surface temperature that do not give rise to changes in net radiative flux fitting the linear model.

I tried to bring out the point about internal cloud oscillations, in writing: «The ordinary least squares (OLS) regression approach used will, however, underestimate Y in the presence of fluctuations in surface temperature that do not give rise to changes in net radiative flux fitting the linear model.

Using a linear regression model as in Allen and Tett this approach yields an objective measure of model - observation goodness - of - fit (via the residual sum of squares weighted by differences expected due to internal variability).

A multiple regression revealed that none of the motivations were substantial predictors of RMT likelihood (r - squared =.04)- although within the weak model, the Relationship motivation was the best predictor.

Ordinary least squares regression was used to test the overall model.

In Tables III and IV, the R - square change associated with each successive model (i.e., with each of the blocks of variables when entered) in the regressions is shown.

Under 2 separate regression models (1 for pubertal status and 1 for age), each variable's partial sums of squares and associated probability were used to examine these effects in the 2 sexes together (Table 1).