iso.summary: Data Summary

In IsoCorr: Correcting Drift and Carry-over in Continuous Isotopic Measurements

Description

Provides the mean and standard error of continuous isotopic measurements.

Usage

iso.summary(x, y, n, skip.inquiry = FALSE)

Arguments

x	Vector with sample names (character). length(x) should equal length(y).
y	Vector with sample values (numeric). length(y) should equal length(x).
n	Number of itterations per sample. length(x) should be a multiplicate of n.
skip.inquiry	Surpres inquiries regarding possible errors, irrespective of possible NAs (No Nas should be present as 'iso.summary' should always be used after 'drift' and 'carry.over', both of which fix NAs). Default setting is FALSE when undifined.

Value

Returns a three-column data frame. First column contains sample names (factor), second column contains sample means (numeric), third column contains standard errors of the samples (numeric).

Author(s)

J.D.M.S.

Examples

data("Iso_data")

## Example
names <- Iso_data$Identifier[1:312]
values <- Iso_data$d.D_H.Mean[1:312]

cor_data <- cbind.data.frame(names,values)
# 5 itterations is enough for this dataset, 10 are used to illustrate convergence
for(i in 1:10){
  cor_data <- drift(cor_data[,1], as.numeric(cor_data[,2]), 8,
              "LAB2", -48.7, graph = TRUE, skip.inquiry = TRUE)
  cor_data <- carry.over(cor_data[,1], as.numeric(cor_data[,2]), 8,
              c("LAB1","LAB3"), c(7.7, -147), graph = TRUE, skip.inquiry = TRUE)
}

sum_dat <- iso.summary(cor_data[,1], as.numeric(cor_data[,2]), 8, skip.inquiry = TRUE)

IsoCorr documentation built on Jan. 8, 2021, 2:13 a.m.