Cameca | R Documentation |
Cameca
default CAMECA diagnostics
CooksD
regression diagnostics based on Cook's D
Cameca( .IC, .ion1, .ion2, ..., .X = NULL, .N = NULL, .species = NULL, .t = NULL, .output = "complete", .alpha_level = 0.05, .hyp = "none", .mc_cores = 1 ) CooksD( .IC, .ion1, .ion2, ..., .X = NULL, .N = NULL, .species = NULL, .t = NULL, .output = "complete", .hyp = "none", .alpha_level = 0.05, .mc_cores = 1 ) CV( .IC, .ion1, .ion2, ..., .X = NULL, .N = NULL, .species = NULL, .t = NULL, .output = "complete", .hyp = "none", .alpha_level = 0.05, .mc_cores = 1 ) Rm( .IC, .ion1, .ion2, ..., .X = NULL, .N = NULL, .species = NULL, .t = NULL, .output = "complete", .hyp = "none", .alpha_level = 0.05, .mc_cores = 1 ) norm_E( .IC, .ion1, .ion2, ..., .X = NULL, .N = NULL, .species = NULL, .t = NULL, .output = "complete", .hyp = "none", .alpha_level = 0.05, .mc_cores = 1 ) QQ( .IC, .ion1, .ion2, ..., .X = NULL, .N = NULL, .species = NULL, .t = NULL, .output = "complete", .hyp = "none", .alpha_level = 0.05, .mc_cores = 1 ) IR( .IC, .ion1, .ion2, ..., .X = NULL, .N = NULL, .species = NULL, .t = NULL, .output = "complete", .hyp = "none", .alpha_level = 0.05, .mc_cores = 1 )
.IC |
A tibble containing processed ion count data. |
.ion1 |
A character string constituting the heavy isotope ("13C"). |
.ion2 |
A character string constituting the light isotope ("12C"). |
... |
Variables for grouping. |
.X |
A variable constituting the ion count rate (defaults to
variables generated with |
.N |
A variable constituting the ion counts (defaults to variables
generated with |
.species |
A variable constituting the species analysed (defaults to
variables generated with |
.t |
A variable constituting the time of the analyses (defaults to
variables generated with |
.output |
Character string determining whether the returned values in a minimal version '"flag"' (original dataset + diagnostics) or an extended version with all the intermediate steps of ion- and isotope-wise summary statistics '"complete"'. |
.alpha_level |
The significance level of the hypothesis test and rejection level for outliers. |
.hyp |
Hypothesis test appropriate for the selected method. |
.mc_cores |
Number of workers for parallel execution (Does not work on Windows). |
These functions perform a specific set of diagnostics to term anomalous
values in raw ion count data of an isotope pair. The wrapper function
diag_R
is more convenient as it defines all the ion- and isotope-wise
statistics required for the diagnostics.
A tibbletibble()
containing either the
original dataset with new columns related to the diagnostics or only the
diagnostics. The flag variable enables convenient filtering of the original
tibble for an augmentation of the original dataset.
# Descriptive an predictive statistics for 13C/12C ratios (note .output # argument and remove zero count analysis) tb_R <- stat_R(real_IC, "13C", "12C", file.nm, sample.nm, .output = "complete", .zero = TRUE) # CAMECA style augmentation of ion count data for isotope ratios Cameca(tb_R, "13C", "12C", file.nm, .X = Xt.pr, .N = N.pr, .species = species.nm, .t = t.nm, .output = "flag")
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