ISEtools (version 3.2.0)

ISEtools-package: Ion Selective Electrodes Analysis Methods

Description

Bayesian calibration for single or multiple ISEs using R and OpenBUGS (or JAGS). Estimation of analyte activities using single ISEs or ISE arrays.

Author

Peter Dillingham [aut, cre], Christina McGraw [ctb], Aleksandar Radu [ctb], Basim Alsaedi [ctb]

Maintainer: Peter Dillingham <[e-mail]>

Details

Package:	ISEtools
Type:	Package
Version:	3.2.0
Depends: R (>4.1.0)	Date:
2022-10-14	License:
GPL-2	SystemRequirements: OpenBUGS (>3.0) or JAGS (>=4.3.1)

The primary funtions are loadISEdata (which loads calibration and experimental data from tab-delimited text files), describeISE (uses Bayesian calibration to estimate ISE parameters from calibration data), and analyseISE (combines calibration data with experimental data in basic or standard addition format to estimate analyte concentrations).

References

Dillingham, P.W., Radu, T., Diamond, D., Radu, A. and McGraw, C.M. (2012). Bayesian Methods for Ion Selective Electrodes. Electroanalysis, 24, 316-324. <doi:10.1002/elan.201100510>

Dillingham, P.W., Alsaedi, B.S.O. and McGraw, C.M. (2017). Characterising uncertainty in instrumental limits of detection when sensor response is non-linear. 2017 IEEE SENSORS, Glasgow, United Kingdom, pp. 1-3. <doi:10.1109/ICSENS.2017.8233898>

Dillingham, P.W., Alsaedi, B.S.O., Radu, A., and McGraw, C.M. (2019). Semi-automated data analysis for ion-selective electrodes and arrays using the R package ISEtools. Sensors 19(20), 4544. <doi:10.3390/s19204544>

Dillingham, P.W., Alsaedi, B.S.O., Granados-Focil, S., Radu, A., and McGraw, C.M. (2020). Establishing meaningful Limits of Detection for ion-selective electrodes and other nonlinear sensors ACS Sensors, 5, 250-257. <doi:10.1021/acssensors.9b02133>

Examples

data(LeadStdAdd)
print(LeadStdAdd)
summary(LeadStdAdd)
plot(LeadStdAdd)
# \donttest{
example1 = describeISE(LeadStdAdd, Z =2, temperature=21)
print(example1)
summary(example1)
plot(example1)
example2 = analyseISE(LeadStdAdd, Z =2, temperature=21)
print(example2)
summary(example2)
plot(example2, ylim = c(-7, -3), xlab = "ID (Sample)", 
	ylab = expression(paste(log[10], " ", Pb^{paste("2","+",sep="")} )))
# }