R: Weighted Regression for Water Quality Evaluation in Tidal Waters

# Weighted Regression for Water Quality Evaluation in Tidal Waters

## Documentation for package ‘WRTDStidal’ version 1.1.5

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

A C D F G K L M N O P R S T W

## -- A --

aiccrq | Akaike's Information Criterion for weighted quantile regression
all_sims | Simulate a response variable time series using all functions
annual_agg | Create annual aggregations of WRTDS output
annual_agg.default | Create annual aggregations of WRTDS output

## -- C --

chldat | Monthly chlorophyll time series for Hillsborough Bay
chllab | Chlorophyll axis label
chngest | Get trend for a single time period
createsrch | Create a grid of half-window widths to evaluate

## -- D --

daydat | Daily chlorophyll, salinity, and discharge time series for the Upper Patuxent River Estuary
dec_time | Create decimal time from time vector
dec_time.Date | Create decimal time from time vector
dynaplot | Plot model response to salinity or flow as a lineplot for all months
dynaplot.tidal | Plot model response to salinity or flow as a lineplot for all months
dynaplot.tidalmean | Plot model response to salinity or flow as a lineplot for all months

## -- F --

fillpo | Fill the 'predonobs' attribute
fillpo.tidal | Fill the 'predonobs' attribute
fillpo.tidalmean | Fill the 'predonobs' attribute
fill_grd | Add date columns and fill missing values in the interpolation grids
fitmoplot | Plot the fitted results for a tidal object by month
fitmoplot.tidal | Plot the fitted results for a tidal object by month
fitmoplot.tidalmean | Plot the fitted results for a tidal object by month
fitplot | Plot the fitted results for a tidal object
fitplot.tidal | Plot the fitted results for a tidal object
fitplot.tidalmean | Plot the fitted results for a tidal object

## -- G --

getwts | Get weights for regression
getwts.default | Get weights for regression
goodfit | Quantile regression goodness of fit
gradcols | Get colors for plots
gridplot | Plot variable response to salinity/flow as a gridded surface for all months
gridplot.tidal | Plot variable response to salinity/flow as a gridded surface for all months
gridplot.tidalmean | Plot variable response to salinity/flow as a gridded surface for all months

## -- K --

kendallSeasonalTrendTest | Kendall seasonal trend test
kendallSeasonalTrendTest.data.frame | Kendall seasonal trend test
kendallSeasonalTrendTest.default | Kendall seasonal trend test
kendallSeasonalTrendTest.formula | Kendall seasonal trend test
kendallSeasonalTrendTest.matrix | Kendall seasonal trend test
kendallTrendTest | Kendall trend test
kendallTrendTest.default | Kendall trend test
kendallTrendTest.formula | Kendall trend test

## -- L --

lnQ_sim | Simulate a discharge time series
lnres_err | Simulate random errors from a time series
lnres_sim | Simulate a water quality time series

## -- M --

modfit | Fit weighted regression and get predicted/normalized response variable
modfit.data.frame | Fit weighted regression and get predicted/normalized response variable
modfit.default | Fit weighted regression and get predicted/normalized response variable
modfit.tidal | Fit weighted regression and get predicted/normalized response variable
modfit.tidalmean | Fit weighted regression and get predicted/normalized response variable

## -- N --

nobsplot | Plot number of observations in a WRTDS interpolation grid
nobsplot.default | Plot number of observations in a WRTDS interpolation grid
nobsplot.tidal | Plot number of observations in a WRTDS interpolation grid
nobsplot.tidalmean | Plot number of observations in a WRTDS interpolation grid

## -- O --

obsplot | Plot observed response variable and salinity/flow data
obsplot.default | Plot observed response variable and salinity/flow data
obsplot.tidal | Plot observed response variable and salinity/flow data
obsplot.tidalmean | Plot observed response variable and salinity/flow data

## -- P --

prdnrmplot | Plot combined predicted and normalized results from a tidal object
prdnrmplot.tidal | Plot combined predicted and normalized results from a tidal object
prdnrmplot.tidalmean | Plot combined predicted and normalized results from a tidal object

## -- R --

resnorm | Get salinity/flow normalized WRTDS predictions from interpolation grids
resnorm.tidal | Get salinity/flow normalized WRTDS predictions from interpolation grids
resnorm.tidalmean | Get salinity/flow normalized WRTDS predictions from interpolation grids
respred | Get WRTDS predictions from interpolation grids
respred.tidal | Get WRTDS predictions from interpolation grids
respred.tidalmean | Get WRTDS predictions from interpolation grids
resscls | Get the scale parameters for predicted values
resscls.tidalmean | Get the scale parameters for predicted values

## -- S --

samp_sim | Sample a daily time series at a set frequency
seasplot | Plot seasonal trends across all years
seasplot.tidal | Plot seasonal trends across all years
seasplot.tidalmean | Plot seasonal trends across all years
seasyrplot | Plot seasonal model response by years
seasyrplot.tidal | Plot seasonal model response by years
seasyrplot.tidalmean | Plot seasonal model response by years
sliceplot | Plot time slices within a tidal object
sliceplot.tidal | Plot time slices within a tidal object
sliceplot.tidalmean | Plot time slices within a tidal object

## -- T --

tidal | Create a tidal class object
tidalmean | Create a tidalmean class object
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

## -- W --

winsrch_constrOptim | Find the optimal half-window width combination
winsrch_constrOptim.default | Find the optimal half-window width combination
winsrch_grid | Evaluate half-window width combinations
winsrch_grid.default | Evaluate half-window width combinations
winsrch_optim | Find the optimal half-window width combination
winsrch_optim.default | Find the optimal half-window width combination
wrtds | Get WRTDS prediction grid
wrtds.tidal | Get WRTDS prediction grid
wrtds.tidalmean | Get WRTDS prediction grid
wrtdscv | Use k-fold cross-validation to evaluate WRTDS model fit
wrtdscv.default | Use k-fold cross-validation to evaluate WRTDS model fit
wrtdsperf | Get WRTDS performance metrics
wrtdsperf.tidal | Get WRTDS performance metrics
wrtdsperf.tidalmean | Get WRTDS performance metrics
wrtdsrsd | Get WRTDS residuals
wrtdsrsd.tidal | Get WRTDS residuals
wrtdsrsd.tidalmean | Get WRTDS residuals
wrtdstrnd | Get WRTDS trends
wrtdstrnd.default | Get WRTDS trends
wrtdstrnd.tidal | Get WRTDS trends
wrtdstrnd.tidalmean | Get WRTDS trends
wrtdstrnd_sk | Get WRTDS trends using seasonal Kendall tests
wrtdstrnd_sk.default | Get WRTDS trends using seasonal Kendall tests
wrtdstrnd_sk.tidal | Get WRTDS trends using seasonal Kendall tests
wrtdstrnd_sk.tidalmean | Get WRTDS trends using seasonal Kendall tests
wtsplot | Plot the weights for an observation
wtsplot.default | Plot the weights for an observation
wtsplot.tidal | Plot the weights for an observation
wtsplot.tidalmean | Plot the weights for an observation