Author: Yu Gao(gaoyu19920914@gmail.com)
Date: 2026-06-01

# BetaStability with rioja datasets

#### Yu Gao(gaoyu19920914@gmail.com)

#### 2026-06-01

# BetaStability with rioja datasets

This vignette demonstrates the BetaStability package using `linearPred` with the Ponds dataset from the rioja package.

## Installation

First, install the package from GitHub:

    # Install from GitHub
    # install.packages("devtools")
    # devtools::install_github("gaoyu19920914/betaStability")

    # OR install from BioConductor (in the future when it's available)
    # if (!requireNamespace("BiocManager", quietly = TRUE))
    #     install.packages("BiocManager")
    # BiocManager::install("betaStability")

## Loading Required Packages

Load the BetaStability package and the rioja package for test data:

    library(betaStability)
    library(vegan)
    library(ggplot2)
    # Check if rioja is available and install it to load dataset
    if (!requireNamespace("rioja", quietly = TRUE)) install.packages("rioja")
    data("Ponds", package = "rioja")

### rioja dataset with linearPred

    comtable <- Ponds$spec
    envmeta <- Ponds$env[, 6:19]

    # Calculate stability with linearPred
    stability_rioja_linear <- betaStability(
        comtable = comtable,
        envmeta = envmeta,
        method = "linearPred"
    )

    # Inspect the result
    head(stability_rioja_linear)
    #>    stability_Linear
    #> 4       -0.03592404
    #> 7        0.11670026
    #> 31       0.06042562
    #> 34       0.04890066
    #> 37       0.03335611
    #> 42      -0.08761045
    p_rioja <- plotStability(stability_rioja_linear, sitenames = Ponds$env$Name)
    p_rioja

    print(sessionInfo())
    #> R version 4.5.3 (2026-03-11 ucrt)
    #> Platform: x86_64-w64-mingw32/x64
    #> Running under: Windows 11 x64 (build 26200)
    #>
    #> Matrix products: default
    #>   LAPACK version 3.12.1
    #>
    #> locale:
    #> [1] LC_COLLATE=C
    #> [2] LC_CTYPE=English_United States.utf8
    #> [3] LC_MONETARY=English_United States.utf8
    #> [4] LC_NUMERIC=C
    #> [5] LC_TIME=English_United States.utf8
    #>
    #> time zone: Asia/Shanghai
    #> tzcode source: internal
    #>
    #> attached base packages:
    #> [1] stats     graphics  grDevices utils     datasets  methods   base
    #>
    #> other attached packages:
    #> [1] ggplot2_4.0.2       vegan_2.7-3         permute_0.9-10
    #> [4] betaStability_0.0.4
    #>
    #> loaded via a namespace (and not attached):
    #>  [1] sass_0.4.10          generics_0.1.4       shape_1.4.6.1
    #>  [4] stringi_1.8.7        lattice_0.22-9       usedist_0.4.0
    #>  [7] digest_0.6.39        magrittr_2.0.4       rioja_1.0-7
    #> [10] evaluate_1.0.5       grid_4.5.3           RColorBrewer_1.1-3
    #> [13] BBmisc_1.13.1        iterators_1.0.14     fastmap_1.2.0
    #> [16] xgboost_3.2.1.1      glmnet_4.1-10        Matrix_1.7-5
    #> [19] foreach_1.5.2        doParallel_1.0.17    plyr_1.8.9
    #> [22] jsonlite_2.0.0       backports_1.5.0      survival_3.8-6
    #> [25] mgcv_1.9-4           scales_1.4.0         pbapply_1.7-4
    #> [28] codetools_0.2-20     jquerylib_0.1.4      cli_3.6.5
    #> [31] rlang_1.1.7          splines_4.5.3        withr_3.0.2
    #> [34] cachem_1.1.0         yaml_2.3.12          otel_0.2.0
    #> [37] tools_4.5.3          parallel_4.5.3       reshape2_1.4.5
    #> [40] checkmate_2.3.4      dplyr_1.2.0          gdm_1.6.0-7
    #> [43] vctrs_0.7.2          R6_2.6.1             lifecycle_1.0.5
    #> [46] randomForest_4.7-1.2 stringr_1.6.0        MASS_7.3-65
    #> [49] cluster_2.1.8.2      pkgconfig_2.0.3      pillar_1.11.1
    #> [52] bslib_0.10.0         gtable_0.3.6         data.table_1.18.2.1
    #> [55] glue_1.8.0           Rcpp_1.1.1           xfun_0.57
    #> [58] tibble_3.3.1         tidyselect_1.2.1     rstudioapi_0.18.0
    #> [61] knitr_1.51           farver_2.1.2         nlme_3.1-169
    #> [64] htmltools_0.5.9      labeling_0.4.3       rmarkdown_2.31
    #> [67] compiler_4.5.3       S7_0.2.1