Package: wqtrends 1.5.0

wqtrends: Assess Water Quality Trends with Generalized Additive Models

Assess Water Quality Trends for Long-Term Monitoring Data in Estuaries using Generalized Additive Models following Wood (2017) <doi:10.1201/9781315370279> and Error Propagation with Mixed-Effects Meta-Analysis following Sera et al. (2019) <doi:10.1002/sim.8362>. Methods are available for model fitting, assessment of fit, annual and seasonal trend tests, and visualization of results.

Authors:Marcus Beck [aut, cre], Perry de Valpine [aut], Rebecca Murphy [aut], Ian Wren [aut], Ariella Chelsky [aut], Melissa Foley [aut], David Senn [aut]

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NEWS

# Install 'wqtrends' in R:
install.packages('wqtrends', repos = c('https://fawda123.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tbep-tech/wqtrends/issues

Datasets:
  • rawdat - Raw data from San Francisco Estuary

On CRAN:

reportingsan-francisco-baytime-series-analysiswater-quality

5.98 score 10 stars 24 scripts 156 downloads 26 exports 73 dependencies

Last updated 2 months agofrom:43dec3c548. Checks:OK: 7. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-winOKNov 03 2024
R-4.5-linuxOKNov 03 2024
R-4.4-winOKNov 03 2024
R-4.4-macOKNov 03 2024
R-4.3-winOKNov 03 2024
R-4.3-macOKNov 03 2024

Exports:anlz_avgseasonanlz_backtransanlz_fitanlz_gamanlz_metseasonanlz_mixmetaanlz_perchganlz_prdanlz_prddayanlz_prdmatrixanlz_pvalformatanlz_smoothanlz_sumstatsanlz_sumtrndseasonanlz_transanlz_trndseasonshow_metseasonshow_mettrndseasonshow_perchgshow_prd3dshow_prddoyshow_prdseasonshow_prdseriesshow_sumtrndseasonshow_sumtrndseason2show_trndseason

Dependencies:askpassbase64encbslibcachemclicolorspacecpp11crosstalkcurldata.tabledigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelubridatemagrittrMASSMatrixmemoisemgcvmimemixmetamunsellnlmeopensslpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcpprlangrmarkdownsassscalesstringistringrsystibbletidyrtidyselecttimechangetinytexutf8vctrsviridisLitewithrxfunyaml

Getting started

Rendered fromwqtrends.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-09-03
Started: 2024-02-15

Readme and manuals

Help Manual

Help pageTopics
Extract period (seasonal) averages from fitted GAManlz_avgseason
Back-transform response variableanlz_backtrans
Return summary statistics for GAM fitsanlz_fit
Fit a generalized additive model to a water quality time seriesanlz_gam
Extract period (seasonal) metrics from fitted GAManlz_metseason
Fit a mixed meta-analysis regression model of trendsanlz_mixmeta
Estimate percent change trends from GAM results for selected time periodsanlz_perchg
Get predicted data from fitted GAMs across period of observationanlz_prd
Get predicted data from fitted GAMs across period of observation, every dayanlz_prdday
Get prediction matrix for a fitted GAManlz_prdmatrix
Format p-values for show functionsanlz_pvalformat
Return summary statistics for smoothers of GAMsanlz_smooth
Retrieve summary statistics for seasonal metrics and trend resultsanlz_sumstats
Estimate seasonal rates of change based on average estimates for multiple window widthsanlz_sumtrndseason
Transform response variableanlz_trans
Estimate rates of change based on seasonal metricsanlz_trndseason
Raw data from San Francisco Estuary (South Bay)rawdat
Plot period (seasonal) averages from fitted GAMshow_metseason
Plot seasonal metrics and rates of changeshow_mettrndseason
Plot percent change trends from GAM results for selected time periodsshow_perchg
Plot a 3-d surface of predictionsshow_prd3d
Plot predictions for GAMs against day of yearshow_prddoy
Plot predictions for GAMs over time, by seasonshow_prdseason
Plot predictions for GAMs over time seriesshow_prdseries
Plot seasonal rates of change based on average estimates for multiple window widthsshow_sumtrndseason
Plot seasonal rates of change in quarters based on average estimates for multiple window widthsshow_sumtrndseason2
Plot rates of change based on seasonal metricsshow_trndseason