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WRTDStidal (version 1.1.4)

Weighted Regression for Water Quality Evaluation in Tidal Waters

Description

An adaptation for estuaries (tidal waters) of weighted regression on time, discharge, and season to evaluate trends in water quality time series. Please see Beck and Hagy (2015) for details.

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Version

Install

install.packages('WRTDStidal')

Monthly Downloads

207

Version

1.1.4

License

CC0

Maintainer

Marcus W. Beck

Last Published

October 20th, 2023

Functions in WRTDStidal (1.1.4)

getwts

Get weights for regression
fillpo

Fill the predonobs attribute
kendallTrendTest

Kendall trend test
gridplot

Plot variable response to salinity/flow as a gridded surface for all months
goodfit

Quantile regression goodness of fit
lnQ_sim

Simulate a discharge time series
prdnrmplot

Plot combined predicted and normalized results from a tidal object
resnorm

Get salinity/flow normalized WRTDS predictions from interpolation grids
obsplot

Plot observed response variable and salinity/flow data
lnres_err

Simulate random errors from a time series
nobsplot

Plot number of observations in a WRTDS interpolation grid
resscls

Get the scale parameters for predicted values
respred

Get WRTDS predictions from interpolation grids
lnres_sim

Simulate a water quality time series
modfit

Fit weighted regression and get predicted/normalized response variable
tidfit

Monthly chlorophyll time series for Hillsborough Bay as a tidal object
tidfitmean

Monthly chlorophyll time series for Hillsborough Bay as a tidal object for the conditional mean model
tidobj

Monthly chlorophyll time series for Hillsborough Bay as a tidal object
tidobjmean

Monthly chlorophyll time series for Hillsborough Bay as a tidal object, conditional mean model
samp_sim

Sample a daily time series at a set frequency
seasplot

Plot seasonal trends across all years
sliceplot

Plot time slices within a tidal object
seasyrplot

Plot seasonal model response by years
wrtds

Get WRTDS prediction grid
wrtdsrsd

Get WRTDS residuals
winsrch_optim

Find the optimal half-window width combination
tidal

Create a tidal class object
wrtdscv

Use k-fold cross-validation to evaluate WRTDS model fit
winsrch_constrOptim

Find the optimal half-window width combination
tidalmean

Create a tidalmean class object
wrtdstrnd_sk

Get WRTDS trends using seasonal Kendall tests
wtsplot

Plot the weights for an observation
winsrch_grid

Evaluate half-window width combinations
wrtdstrnd

Get WRTDS trends
wrtdsperf

Get WRTDS performance metrics
createsrch

Create a grid of half-window widths to evaluate
aiccrq

Akaike's Information Criterion for weighted quantile regression
annual_agg

Create annual aggregations of WRTDS output
dec_time

Create decimal time from time vector
chllab

Chlorophyll axis label
daydat

Daily chlorophyll, salinity, and discharge time series for the Upper Patuxent River Estuary
dynaplot

Plot model response to salinity or flow as a lineplot for all months
all_sims

Simulate a response variable time series using all functions
chngest

Get trend for a single time period
chldat

Monthly chlorophyll time series for Hillsborough Bay
fitplot

Plot the fitted results for a tidal object
fitmoplot

Plot the fitted results for a tidal object by month
gradcols

Get colors for plots
fill_grd

Add date columns and fill missing values in the interpolation grids
kendallSeasonalTrendTest

Kendall seasonal trend test