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# allometric
[](https://github.com/allometric/allometric/actions/workflows/check-standard.yaml)
[](https://app.codecov.io/gh/allometric/allometric)
`allometric` provides structured allometric models for predicting tree attributes.
The [documentation website](https://allometric.org) contains model browsing
tools, guides, and additional examples.
## Installation
Install the package from GitHub with `devtools`:
```{r eval=FALSE}
devtools::install_github("allometric/allometric")
```
Install the compiled model distribution locally:
```{r eval=FALSE}
library(allometric)
install_models()
```
The models are downloaded from the public
[models](https://github.com/allometric/models) repository. Load them with:
```{r eval=FALSE}
allometric_models <- load_models()
```
## Example
Select a model and use it to predict stem volume from diameter outside bark at
breast height (`dsob`, in cm) and total stem height (`hst`, in m):
```{r eval=FALSE}
poudel_model <- allometric_models |>
dplyr::filter(pub_id == "poudel_2019") |>
select_model("1bc22c7e")
predict(poudel_model, 12, 65)
#> 0.6231063 [m^3]
```
See the [documentation website](https://allometric.org) for more examples,
model discovery, variable naming, and advanced prediction workflows.
Total Commits: 542
Total Committers: 5
Avg Commits per committer: 108.4
Development Distribution Score (DDS): 0.028
Commits in past year: 26
Committers in past year: 2
Avg Commits per committer in past year: 13.0
Development Distribution Score (DDS) in past year: 0.154
Total issues: 139
Total pull requests: 12
Average time to close issues: 30 days
Average time to close pull requests: about 3 hours
Total issue authors: 5
Total pull request authors: 3
Average comments per issue: 0.68
Average comments per pull request: 0.42
Merged pull request: 11
Bot issues: 0
Bot pull requests: 0
Past year issues: 1
Past year pull requests: 4
Past year average time to close issues: 8 days
Past year average time to close pull requests: 27 minutes
Past year issue authors: 1
Past year pull request authors: 2
Past year average comments per issue: 1.0
Past year average comments per pull request: 0.0
Past year merged pull request: 3
Past year bot issues: 0
Past year bot pull requests: 0