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(coming back to t-distribution MLE after robust readings)
motivation: heavy-tailed distribution but not clear outliers
current: TModel, TArma in `miscmodels`, t-based covariance in outlier robus…
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Hi scDesign3 developers,
Thank you for maintaining the amazing tool!
When I was simulating the data from https://www.10xgenomics.com/resources/datasets/mouse-brain-serial-section-2-sagittal-anter…
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The current options for handling correlation are limited.
1) Correlation is either 0 or the maximum possible (perfect for normal).
Allow partial correlations.
2) Some correlations that we…
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The original Proposal Sumary:
> Correlation is a measure of interdependency of variable quantities. A risk-based capital allocation approach heavily relies on the correlations between risks. Correl…
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Following this paper : http://proceedings.mlr.press/v128/messoudi20a.html
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I am currently working with a large model > 2 GB of JSON. This leads to files being large and loading slow due to parsing. Are there any plans to add drivers to save to other formats like HDF5?
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- 经典模型可以参考金光的中文书籍《基于退化的可靠性技术——模型、方法及应用》
- 退化轨道模型是否需要加入?该部分可参考Meeker书籍以及对应的 R 包
- 统计推断方法是否需要考虑:广义推断方法/客观贝叶斯方法?
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https://rdrr.io/rforge/distrMod/man/MDEstimator.html
https://stackoverflow.com/questions/67007706/how-to-calculate-efficient-minimum-distance-in-python-regression
**edit** https://rdrr.io/rforge/f…
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Would it be possible to implement correlated multivariate ordinal models like done in the mvord package (https://cran.r-project.org/web/packages/mvord/vignettes/vignette_mvord.pdf)?
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In a structural equation modeling framework, we often define latent unmeasured variables with indicators. For example
```
library(lavaan)
data(PoliticalDemocracy)
mod |z|)
.x1 …