Set non-detects and unquantified values in residue series without replicates

- - -

This function automates replacing unquantified values in residue time and -depth series. For time series, the function performs part of the residue -processing proposed in the FOCUS kinetics guidance for parent compounds -and metabolites. For two-dimensional residue series over time and depth, -it automates the proposal of Boesten et al (2015).

- -

set_nd_nq(res_raw, lod, loq = NA, time_zero_presence = FALSE)
-
-set_nd_nq_focus(
-  res_raw,
-  lod,
-  loq = NA,
-  set_first_sample_nd = TRUE,
-  first_sample_nd_value = 0,
-  ignore_below_loq_after_first_nd = TRUE
-)

- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

res_raw	Character vector of a residue time series, or matrix of -residue values with rows representing depth profiles for a specific sampling -time, and columns representing time series of residues at the same depth. -Values below the limit of detection (lod) have to be coded as "nd", values -between the limit of detection and the limit of quantification, if any, have -to be coded as "nq". Samples not analysed have to be coded as "na". All -values that are not "na", "nd" or "nq" have to be coercible to numeric
lod	Limit of detection (numeric)
loq	Limit of quantification(numeric). Must be specified if the FOCUS rule to -stop after the first non-detection is to be applied
time_zero_presence	Do we assume that residues occur at time zero? -This only affects samples from the first sampling time that have been -reported as "nd" (not detected).
set_first_sample_nd	Should the first sample be set to "first_sample_nd_value" -in case it is a non-detection?
first_sample_nd_value	Value to be used for the first sample if it is a non-detection
ignore_below_loq_after_first_nd	Should we ignore values below the LOQ after the first -non-detection that occurs after the quantified values?

- -

Value

- -

A numeric vector, if a vector was supplied, or a numeric matrix otherwise

Functions

- - -

set_nd_nq_focus: Set non-detects in residue time series according to FOCUS rules

References

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Boesten, J. J. T. I., van der Linden, A. M. A., Beltman, W. H. -J. and Pol, J. W. (2015). Leaching of plant protection products and their -transformation products; Proposals for improving the assessment of leaching -to groundwater in the Netherlands — Version 2. Alterra report 2630, Alterra -Wageningen UR (University & Research centre)

FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation - Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, - 18 December 2014, p. 251

- -

Examples

# FOCUS (2014) p. 75/76 and 131/132
-parent_1 <- c(.12, .09, .05, .03, "nd", "nd", "nd", "nd", "nd", "nd")
-set_nd_nq(parent_1, 0.02)
#>  [1] 0.12 0.09 0.05 0.03 0.01   NA   NA   NA   NA   NA
parent_2 <- c(.12, .09, .05, .03, "nd", "nd", .03, "nd", "nd", "nd")
-set_nd_nq(parent_2, 0.02)
#>  [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.03 0.01   NA   NA
set_nd_nq_focus(parent_2, 0.02, loq = 0.05)
#>  [1] 0.12 0.09 0.05 0.03 0.01   NA   NA   NA   NA   NA
parent_3 <- c(.12, .09, .05, .03, "nd", "nd", .06, "nd", "nd", "nd")
-set_nd_nq(parent_3, 0.02)
#>  [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.06 0.01   NA   NA
set_nd_nq_focus(parent_3, 0.02, loq = 0.05)
#>  [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.06 0.01   NA   NA
metabolite <- c("nd", "nd", "nd", 0.03, 0.06, 0.10, 0.11, 0.10, 0.09, 0.05, 0.03, "nd", "nd")
-set_nd_nq(metabolite, 0.02)
#>  [1]   NA   NA 0.01 0.03 0.06 0.10 0.11 0.10 0.09 0.05 0.03 0.01   NA
set_nd_nq_focus(metabolite, 0.02, 0.05)
#>  [1] 0.00   NA 0.01 0.03 0.06 0.10 0.11 0.10 0.09 0.05 0.03 0.01   NA
#
-# Boesten et al. (2015), p. 57/58
-table_8 <- matrix(
-  c(10, 10, rep("nd", 4),
-    10, 10, rep("nq", 2), rep("nd", 2),
-    10, 10, 10, "nq", "nd", "nd",
-    "nq", 10, "nq", rep("nd", 3),
-    "nd", "nq", "nq", rep("nd", 3),
-    rep("nd", 6), rep("nd", 6)),
-  ncol = 6, byrow = TRUE)
-set_nd_nq(table_8, 0.5, 1.5, time_zero_presence = TRUE)
#>       [,1]  [,2]  [,3] [,4] [,5] [,6]
-#> [1,] 10.00 10.00  0.25 0.25   NA   NA
-#> [2,] 10.00 10.00  1.00 1.00 0.25   NA
-#> [3,] 10.00 10.00 10.00 1.00 0.25   NA
-#> [4,]  1.00 10.00  1.00 0.25   NA   NA
-#> [5,]  0.25  1.00  1.00 0.25   NA   NA
-#> [6,]    NA  0.25  0.25   NA   NA   NA
-#> [7,]    NA    NA    NA   NA   NA   NA
table_10 <- matrix(
-  c(10, 10, rep("nd", 4),
-    10, 10, rep("nd", 4),
-    10, 10, 10, rep("nd", 3),
-    "nd", 10, rep("nd", 4),
-    rep("nd", 18)),
-  ncol = 6, byrow = TRUE)
-set_nd_nq(table_10, 0.5, time_zero_presence = TRUE)
#>       [,1]  [,2]  [,3] [,4] [,5] [,6]
-#> [1,] 10.00 10.00  0.25   NA   NA   NA
-#> [2,] 10.00 10.00  0.25   NA   NA   NA
-#> [3,] 10.00 10.00 10.00 0.25   NA   NA
-#> [4,]  0.25 10.00  0.25   NA   NA   NA
-#> [5,]    NA  0.25    NA   NA   NA   NA
-#> [6,]    NA    NA    NA   NA   NA   NA
-#> [7,]    NA    NA    NA   NA   NA   NA