mult.latent.reg
Regression and Clustering in Multivariate Response Scenarios
Fitting multivariate response models with random effects on one or two levels; whereby the (one-dimensional) random effect represents a latent variable approximating the multivariate space of outcomes, after possible adjustment for covariates. The method is particularly useful for multivariate, highly correlated outcome variables with unobserved heterogeneities. Applications include regression with multivariate responses, as well as multivariate clustering or ranking problems. See Zhang and Einbeck (2024) doi:10.1007/s42519-023-00357-0.
- Version0.2.1
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release11/15/2024
Team
Yingjuan Zhang
Jochen Einbeck
Show author detailsRolesAuthor, Contributor
Insights
Last 30 days
This package has been downloaded 472 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 4,218 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jan 24, 2025 with 59 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports3 packages