Jaron Arbet
Jaron Arbet
`dfSummary` creates histograms for continuous variables. However, currently the xaxis below the histogram does not contain any tick mark labels, so it is unclear which values correspond to the bars...
`dfSummary` makes histograms for all numeric variables. Would it be possible to have an option to show boxplots instead? That way we could potentially identify outlier observations as dots beyond...
For `run_all_consensus_partition_methods`: > When `top_n` > 5000, the function only randomly sample 5000 rows from `top_n` rows I understand the limitation of 5000 may help computation speed, but would it...
Is it possible to impute mixed numeric/categorical data within `train`'s `preProc` argument? I want to impute within `train`'s cross validation, thereby accounting for how uncertainty in imputations affects estimation of...
I am trying to use `caret` to fit a random forest binary classification model using `OOB` resampling with a custom summary measure. However, I get the following warning: ``` library(caret);...
### Expected behavior For `coxph`, if a predictor has missing values, those subjects are excluded by default. Thus for `ggforest`, I would expect the sample size to show the number...
I have a question about the notation you are using for `lme4::lmer`. Consider [your example](https://datalorax.github.io/equatiomatic/articles/lme4-lmer.html#unconditional-models):  Why did you parameterize *multiple* variances for the random intercepts as $\sigma^2_{\alpha_j}$ for $j=1,...,J$...
When the number of predictors is large, `model.matrix` quickly blows up memory when using the formula interface. For example, I get memory errors when trying to fit a model with...
By default, it seems `skim` truncates long factor levels. Is there an option to print the entire factor level? ``` r suppressPackageStartupMessages(library(skimr)); suppressPackageStartupMessages(library(rchallenge)); data('german', package = 'rchallenge'); # notice the...
It would be super cool to add support for "small sample corrected cluster sandwich standard errors" for a proportional odds (PO) regression model. The PO model works for ordinal categorical...