Sentence examples for many regression from inspiring English sources

This paper exploits many regression discontinuity (RD) designs to estimate heterogeneous effects of public insurance eligibility.

There are, however, many regression discontinuity cases where multiple scores have to cross all of their cutoffs to get treated.

As single trees are assumed to be prone to errors, RFR builds many regression trees (i.e. a forest) from random subsets of the input data and validates the results on the withheld data.

One example of this is below-ground root biomass, where many regression equations have been produced to predict live root biomass based on a ratio of the above-ground biomass [64, 65].

This type of penalty is known indeed to promote sparsity, i.e., to force many regression coefficients to be zero; this obviates the need for pre-selection of the data.

Many regression models used to estimate cumulative incidence functions will assume proportional hazards.

Further, we applied a z-score transformation (adjusting each observation to the mean and scaling by the standard deviation) in order to compare odds ratios from the many regressions.

Besides these two standard approaches to GWAS, many regression-based models for associating phenotype and genotype have been proposed, such as Lasso models (e.g. Kim et al., 2009).

However, one of the robustness tests (excluding studies with many regressions) suggests that fuelwood and LPG price do influence fuel choices.

However, many other regression methods are available and can be used to solve the regression problem.

Many multivariate regression techniques are designed for univariate response cases.