This function uses an autoregressive model to produce more accurate estimates of concentration and flux
Arguments
- eList
named list with the INFO, Daily, and Sample dataframes and surfaces matrix
- rho
numeric the lag one autocorrelation. Default is 0.9.
- niter
number of iterations. Default is 200.
- seed
integer value. Defaults to NA, which will not change the current seed. Setting the seed to any given value can be used to create repeatable output.
- verbose
logical specifying whether or not to display progress message
Details
This function takes an existing eList Including the estimated model (the surfaces object in the eList) And produces the daily WRTDSKalman estimates of concentration and flux These generated estimates are called genConc and genFlux
Examples
eList <- Choptank_eList
eList <- WRTDSKalman(eList, niter = 10)
#> % complete:
#> 10
#> 20
#> 30
#> 40
#> 50
#> 60
#> 70
#> 80
#> 90
#> 100
summary(eList$Daily)
#> Date Q Julian Month
#> Min. :1979-10-01 Min. : 0.00991 Min. :47389 Min. : 1.000
#> 1st Qu.:1987-09-30 1st Qu.: 0.93446 1st Qu.:50311 1st Qu.: 4.000
#> Median :1995-09-30 Median : 2.40693 Median :53232 Median : 7.000
#> Mean :1995-09-30 Mean : 4.08658 Mean :53232 Mean : 6.523
#> 3rd Qu.:2003-09-30 3rd Qu.: 4.61565 3rd Qu.:56154 3rd Qu.:10.000
#> Max. :2011-09-30 Max. :246.35656 Max. :59076 Max. :12.000
#>
#> Day DecYear MonthSeq Qualifier
#> Min. : 1.0 Min. :1980 Min. :1558 Length:11688
#> 1st Qu.: 93.0 1st Qu.:1988 1st Qu.:1654 Class :character
#> Median :184.0 Median :1996 Median :1750 Mode :character
#> Mean :183.8 Mean :1996 Mean :1749
#> 3rd Qu.:275.0 3rd Qu.:2004 3rd Qu.:1845
#> Max. :366.0 Max. :2012 Max. :1941
#>
#> i LogQ Q7 Q30
#> Min. : 1 Min. :-4.61412 Min. : 0.01808 Min. : 0.09606
#> 1st Qu.: 2923 1st Qu.:-0.06779 1st Qu.: 0.98704 1st Qu.: 1.16949
#> Median : 5844 Median : 0.87835 Median : 2.55661 Median : 2.86850
#> Mean : 5844 Mean : 0.76616 Mean : 4.08569 Mean : 4.08160
#> 3rd Qu.: 8766 3rd Qu.: 1.52945 3rd Qu.: 4.93017 3rd Qu.: 5.69169
#> Max. :11688 Max. : 5.50678 Max. :84.00395 Max. :25.47478
#> NA's :6 NA's :29
#> yHat SE ConcDay FluxDay
#> Min. :-1.790952 Min. :0.1347 Min. :0.1776 Min. : 1.643
#> 1st Qu.:-0.004236 1st Qu.:0.2191 1st Qu.:1.0357 1st Qu.: 98.013
#> Median : 0.130934 Median :0.2504 Median :1.1959 Median : 250.088
#> Mean : 0.120318 Mean :0.2689 Mean :1.1978 Mean : 366.085
#> 3rd Qu.: 0.258944 3rd Qu.:0.3029 3rd Qu.:1.3551 3rd Qu.: 484.360
#> Max. : 0.661543 Max. :0.6146 Max. :1.9666 Max. :5519.450
#>
#> FNConc FNFlux GenFlux GenConc
#> Min. :0.8352 Min. : 77.55 Min. : 1.60 Min. :0.04955
#> 1st Qu.:1.0540 1st Qu.:169.71 1st Qu.: 96.98 1st Qu.:1.00000
#> Median :1.2067 Median :318.61 Median : 247.37 Median :1.20000
#> Mean :1.2004 Mean :362.71 Mean : 377.36 Mean :1.21672
#> 3rd Qu.:1.3314 3rd Qu.:538.44 3rd Qu.: 498.45 3rd Qu.:1.41998
#> Max. :1.6882 Max. :943.75 Max. :11927.06 Max. :2.43000
#>
#All flux values in AnnualResults are expressed as a rate in kg/day
AnnualResults <- setupYears(eList$Daily)
head(AnnualResults)
#> DecYear Q Conc Flux FNConc FNFlux GenConc GenFlux
#> 1 1980.249 4.251937 0.9485403 316.0491 1.0027237 291.2176 0.9664242 318.3866
#> 2 1981.249 2.217248 1.0351962 184.6712 0.9988918 296.7260 0.9978313 173.3971
#> 3 1982.249 3.046039 1.0361327 269.6309 0.9931881 300.7424 1.0940643 290.2776
#> 4 1983.249 4.986713 1.0072716 363.8563 0.9931768 305.5898 1.0306304 365.9152
#> 5 1984.249 5.718146 0.9901927 437.3007 1.0017255 312.2260 1.0279141 456.6785
#> 6 1985.249 1.517457 1.0571854 133.9210 1.0165324 318.5007 1.0402486 129.2930
#> PeriodLong PeriodStart
#> 1 12 10
#> 2 12 10
#> 3 12 10
#> 4 12 10
#> 5 12 10
#> 6 12 10