{ "_id": "6abfad4899f7aa8c6aa59251", "Package": "dendRoAnalyst", "Type": "Package", "Title": "A Tool for Processing and Analyzing Dendrometer Data", "Version": "2.0.0", "Date": "2026-09-27", "Authors@R": "c(\nperson(\"Sugam\", \"Aryal\", email = \"sugam.aryal@fau.de\", role = c(\"aut\", \"cre\", \"dtc\")),\nperson(\"Martin\", \"Häusser\", email = \"martin.haeusser@fau.de\", role = \"aut\"),\nperson(\"Jussi\", \"Grießinger\", email = \"jussi.griessinger@fau.de\", role = \"aut\"),\nperson(\"Ze-Xin\", \"Fan\", email = \"fanzexin@xtbg.org.cn\", role = \"aut\"),\nperson(\"Achim\", \"Bräuning\", email = \"achim.braeuning@fau.de\", role = c(\"aut\", \"dgs\")))", "Description": "Tools for importing, cleaning, analyzing, and visualizing\nhigh-resolution dendrometer data and for linking them with\nclimate data. Dendrometer and climate records can be imported\nwith automatic date-time parsing (read.dendrometer(),\nread.climate()) and checked for a regular temporal resolution\n(reso_dm()). Preprocessing functions detect and correct\nartificial jumps with a threshold-based or an automatic\nchangepoint method (jump.locator()), detect and fill gaps with\nspline, seasonal, or network interpolation\n(dm.na.interpolation(), network.interpolation()), and truncate\nor resample the series (dendro.truncate(), dendro.resample()).\nDaily statistics (daily.data()), the stem-cycle approach\n(phase.sc()), and the zero-growth approach (phase.zg())\nseparate radial growth from reversible stem shrinkage and\nswelling. The function phase.zg() also returns metrics of tree\nwater deficit (TWD) phases, including the event-based ABr\nindex, and the daily drought indices of Peters et al. (2025)\n. Climate data can be summarized at\ndaily and sub-daily scales and attached to daily, phase-level,\nand point-level outputs (dm_add_climate()). Event-based climate\nanalyses, superposed epoch analyses, and adverse-period\nanalyses (dm_event_climate(), dm_epoch_test(), clim.twd())\nrelate tree responses to climate conditions. Seasonal growth\ncan be fitted with Gompertz, logistic, Richards, generalized\nadditive model, LOESS, and spline functions, detrended, and\ncompared among methods (dm.growth.fit(), dm.detrend.fit(),\ndm.growth.evaluate()). Running correlations with climate\n(mov.cor.dm()) and wavelet power and coherence analyses based\non 'WaveletComp' (dm_wavelet(), dm_wavelet_coherence()) are\nalso provided. Most outputs have dedicated plot methods, and an\noptional 'shiny' application (dendroanalyst()) allows the\ncomplete workflow to be run without programming. The\nzero-growth approach follows Zweifel et al. (2016)\n, and the first version of the package\nis described in Aryal et al. (2020)\n.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.1.0", "Packaged": { "Date": "2026-10-02 13:05:46 UTC", "User": "root" }, "Author": "Sugam Aryal [aut, cre, dtc], Martin Häusser [aut], Jussi\nGrießinger [aut], Ze-Xin Fan [aut], Achim Bräuning [aut, dgs]", "Maintainer": "Sugam Aryal ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-02 12:51:46 UTC", "RemoteUrl": "https://github.com/cran/dendRoAnalyst", "RemoteRef": "HEAD", "RemoteSha": "7dab4ab0f4f5a693ac12f14a47b776e32989ce1f", "_user": "cran", "_type": "src", "_file": "dendRoAnalyst_2.0.0.tar.gz", "_fileid": "https://r2.ropensci.org/6a4bace5e856668b37ad933e2f447badbc19e9dce98d65f755e7af7e7d461a29", "_filesize": 4239803, "_sha256": "6a4bace5e856668b37ad933e2f447badbc19e9dce98d65f755e7af7e7d461a29", "_expires": "2027-01-10T13:10:29.000Z", "_created": 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"page": "read.dendrometer", "title": "Reading dendrometer data", "topics": [ "read.dendrometer" ] }, { "page": "reso_dm", "title": "Detect Temporal Resolution and Irregularities in Time Series", "topics": [ "reso_dm" ] }, { "page": "smooth_dm", "title": "Smoothing of Dendrometer Time Series", "topics": [ "smooth_dm" ] }, { "page": "summary.clim_twd_stats", "title": "Summarize clim.twd.stats output", "topics": [ "summary.clim_twd_stats" ] }, { "page": "summary.clim_twd_test", "title": "Summarize clim.twd.test output", "topics": [ "summary.clim_twd_test" ] }, { "page": "summary.dm_epoch", "title": "Summarize a dm_epoch object", "topics": [ "summary.dm_epoch" ] }, { "page": "summary.dm_growth_fit", "title": "Summarize a dm_growth_fit object", "topics": [ "summary.dm_growth_fit" ] }, { "page": "summary.dm_wavelet", "title": "Summarize a dm_wavelet object", "topics": [ "summary.dm_wavelet" ] }, { "page": "summary.dm_wavelet_reconstruct", "title": "Summarize a dm_wavelet_reconstruct object", "topics": [ "summary.dm_wavelet_reconstruct" ] }, { "page": "summary.mov_cor_dm", "title": "Summary method for running dendrometer-climate correlation objects", "topics": [ "summary.mov_cor_dm" ] }, { "page": "twd.maxima", "title": "Locating the maxima of TWD periods", "topics": [ "twd.maxima" ] } ], "_rundeps": [ "askpass", "backports", "base64enc", "bit", "bit64", "blob", "boot", "broom", "bslib", "cachem", "callr", "cellranger", "changepoint", "cli", "clipr", "colorspace", "conflicted", "cpp11", "crayon", "curl", "data.table", "DBI", "dbplyr", "digest", "dplyr", "dtplyr", "evaluate", "farver", "fastmap", "fontawesome", "forcats", "forecast", "fracdiff", "fs", "gargle", "generics", "ggplot2", "glue", "googledrive", "googlesheets4", "gtable", "haven", "highr", "hms", "htmltools", "httr", "ids", "isoband", "jquerylib", "jsonlite", "knitr", "labeling", "lattice", "lifecycle", "lmtest", "lubridate", "magrittr", "MASS", "Matrix", "memoise", "mgcv", "mime", "minpack.lm", "modelr", "moments", "nlme", "nnet", "openssl", "otel", "pillar", "pkgconfig", "prettyunits", "processx", "progress", "ps", "pspline", "purrr", "R6", "ragg", "rappdirs", "RColorBrewer", "Rcpp", "RcppArmadillo", "readr", "readxl", "rematch", "rematch2", "reprex", "rlang", "rmarkdown", "rstudioapi", "rvest", "S7", "sass", "scales", "selectr", "signal", "stringi", "stringr", "sys", "systemfonts", "textshaping", "tibble", "tidyr", "tidyselect", "tidyverse", "timechange", "timeDate", "tinytex", "tzdb", "urca", "utf8", "uuid", "vctrs", "viridisLite", "vroom", "WaveletComp", "withr", "xfun", "xml2", "yaml", "zoo" ], "_vignettes": [ { "source": "dendRoAnalyst_vignettes.Rmd", "filename": "dendRoAnalyst_vignettes.html", "title": "dendRoAnalyst: end-to-end workflow and function tour", "author": "Package vignette", "engine": "knitr::rmarkdown", "headings": [ "Overview", "Example datasets", "1. Reading dendrometer and climate data", "read.dendrometer()", "read.climate()", "2. Looking for jumps or gaps in dendrometer data", "reso_dm()", "jump.locator() and i.jump.locator()", "dm.na.interpolation() and its plot methods", "3. Resample and truncate the dataset", "dendro.resample()", "dendro.truncate()", "4. Smoothing", "smooth_dm()", "5. Daily approach and daily climate functions", "daily.data() and plot.daily_output()", "dm_daily_clim() and dm_join_daily_clim()", "dm_add_climate() for daily outputs", "6. Stem-cycle approach and associated functions", "phase.sc() and plot.SC_output()", "dm_subdaily_clim(), dm_join_subdaily_clim(), dm_join_phase_clim(), and dm_add_climate()", "7. Zero-growth approach and associated functions", "phase.zg(), twd.maxima(), and plot.ZG_output()", "Climate joins and climate-phase plots", "8. Superposed epoch and associated functions", "dm_event_times(), dm_epoch_extract(), dm_epoch_test(), and method dispatch", "9. Event-based climate functions", "10. Growth fit and evaluation", "dm.fit.gompertz()", "dm.growth.fit(), plot.dm_growth_fit(), and print/summary methods", "dm.growth.fit.double() and dm.growth.evaluate()", "11. Detrending and associated functions", "dm_standardize() and plot.dm_standardized()", "12. Moving correlations and associated functions", "13. Harsh climate using clim.twd() and associated functions", "14. Network interpolation", "network.interpolation() and plot.network_interpolation()", "15. Wavelet analysis and associated functions", "dm_wavelet(), summary.dm_wavelet(), and plot.dm_wavelet()", "dm_wavelet_reconstruct() and its methods", "dm_wavelet_coherence() and plot.dm_wavelet_coherence()", "Closing note", "For suggestions, comments and questions please contact : sugam.aryal@fau.de" ], "created": "2020-07-03 18:00:07", "modified": "2026-10-02 12:51:46", "commits": 4 }, { "source": "NEWS.Rmd", "filename": "NEWS.html", "title": "News in latest version of 'dendRoAnalyst' package", "author": "Sugam Aryal", "engine": "knitr::rmarkdown", "headings": [ "What's new in dendRoAnalyst 0.1.6", "1. Core phase engines are now more modular", "2. Dedicated plotting methods for phase outputs", "3. Expanded data import, checking, and quality control", "4. New and upgraded gap-handling tools", "5. Data conditioning tools are broader and clearer", "6. Daily summaries are now easier to compute and inspect", "7. Climate joining helpers support both daily and subdaily workflows", "8. Event-based phase and climate tools were added", "9. Growth modelling is more flexible and easier to evaluate", "10. Detrending is now better linked to growth fitting", "11. Superposed epoch analysis now has a fuller toolkit", "12. Wavelet tools were added for time-frequency analysis", "13. Moving climate–growth correlations were upgraded", "14. Harsh-climate analysis is more complete", "15. Package design now emphasizes compute-first, plot-second workflows", "Heads-up on namespaces", "In short" ], "created": "2024-03-20 02:30:43", "modified": "2026-05-20 16:02:00", "commits": 2 } ], "_score": 3.494154594018443, "_indexed": true, "_nocasepkg": "dendroanalyst", "_universes": [ "cran" ], "_previous": "0.1.6", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "2.0.0", "date": "2026-10-02T13:08:37.000Z", "distro": "resolute", "commit": "7dab4ab0f4f5a693ac12f14a47b776e32989ce1f", "fileid": "https://r2.ropensci.org/2c05f4bb211e3e199e161ed2a79196ef35515278502841ac8e4731f801632116", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/37010272305" }, { "r": "4.6.1", "os": "linux", "version": "2.0.0", "date": "2026-10-02T13:08:52.000Z", "distro": "resolute", "commit": "7dab4ab0f4f5a693ac12f14a47b776e32989ce1f", "fileid": "https://r2.ropensci.org/6080ea256fece17961345a15cd50556bbb6e109d4d8a577867df178c9124a069", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/37010272305" }, { "r": "4.6.0", "os": "wasm", "version": "2.0.0", "date": "2026-10-02T13:09:04.000Z", "commit": "7dab4ab0f4f5a693ac12f14a47b776e32989ce1f", "fileid": "https://r2.ropensci.org/858226febd662e19cfb96c6ab8d3d4a3f1f8bcd08fc32656d06494cffc4a2c2a", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/37010272305" }, { "r": "4.7.0", "os": "win", "version": "2.0.0", "date": "2026-10-02T13:07:29.000Z", "commit": "7dab4ab0f4f5a693ac12f14a47b776e32989ce1f", "fileid": "https://r2.ropensci.org/ad0d885f2dbbddf5485e13fb2a84472e6cad7319f6c1674fac5d5d4f2ad138b5", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/37010272305" }, { "r": "4.6.1", "os": "win", "version": "2.0.0", "date": "2026-10-02T13:08:01.000Z", "commit": "7dab4ab0f4f5a693ac12f14a47b776e32989ce1f", "fileid": "https://r2.ropensci.org/e4ce92955f34e44fca3bf328e45f0fa13414aeb0c5350847c9a701381bebad20", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/37010272305" } ] }