Sentence examples for maximum likelihood regression from inspiring English sources

Using this transformation, the study ran the maximum likelihood regression to create the GPS model for each country.

Further, a maximum likelihood regression of GDP per capita is run against each subindex for past years, allowing for different coefficients for each stage of development.

This study aims to develop a maximum likelihood regression tree-based model to predict subway incident delays, which are major negative impacts caused by subway incidents from the commuter's perspective.

Analysis using TBSS combined with a maximum likelihood regression with random effects of the fornix, the corpus callosum, and the cingulum identified significant differences between these two types of MCI patients in fractional anisotropy (FA) and radial diffusivity (DR).

In the process of estimating the conditional expectation of the selected outcomes, the study ran a maximum likelihood regression to ascertain the effects of certain of the covariates on the treatment and to create the GPS.

Weng et al. [91] developed a maximum likelihood regression tree-based model to predict subway incident delays, which is beneficial for subway engineers looking to propose effective strategies for reducing subway incident delays, especially in cities with huge public travel demand.

The relationship between the ESG score and ROE is reported in specifications (1 - 5), viz. the two types of pooled OLS, random effect panel, fixed effect panel and quasi-maximum likelihood regression, respectively.

The quadratic relationship of the ESG disclosure scores with ROE is reported in specifications (1 -(4) for the pooled OLS, random effect panel, fixed effect panel and quasi-maximum likelihood regression, respectively.

A problem with the traditional approach is that the experimental error estimation from the maximum-likelihood regression cannot be unbiased, without using replicates.

Two methods of deconvolution were examined for determining the historical incidence of HIV infection, G s): AIDS deaths were modelled using a maximum-likelihood regression approach [8][8] and observed mortality in a given year was assumed to follow a Poisson distribution.

A goodness-of-fit test was applied to each model, and if significant overdispersion was detected, we used negative binomial maximum-likelihood regression (Glynn and Buring 1996).