1.5. Literature¶
AKU, 2008. Moderne Routine- und Schnellmethoden zur Bestimmung von Sr-89 und Sr-90 bei der Umweltüberwachung. Bericht einer Ad-hoc-Arbeitsgruppe des Arbeitskreises Umweltüberwachung (AKU). Bericht FS-08-147-AKU des Fachverbandes für Strahlenschutz. TÜV Media GmbH, Köln.
Barlow, R.J., 1999: Statistics. A Guide to the Use of Statistical Methods in the Physical Sciences. The Manchester Physics Series. John Wiley & Sons Ltd., Chichester, New York, 204 S.
Blobel, V., Lohrmann, E., 1998. Statistische und numerische Methoden der Datenanalyse. B.G. Teubner Stuttgart-Leipzig, 358 S.
Brandt, S., 1999: Datenanalyse. Mit statistischen Methoden und Computerprogrammen; 4. Auflage. Spektrum, Akademischer Verlag, Heidelberg-Berlin, 646 S.
Cox, M.G., Harris, P.M., 2001: Measurement Uncertainty and the Propagation of distributions. NPL, UK, Paper presented at the 10th International Metrology Congress, Saint-Louis, France, 22-25th October 2001.
Cox, M.G., Forbes, A.B., Harris, P.M., Smith, I.M., 2004: The classification and solution of regression problems for calibration. NPL Report CMSC 24/03, (chapter 6.3), National Physics Laboratory, Teddington, UK, 46
http://www.npl.co.uk/ssfm/download/nplreports.html.
Cox, M., Harris, P., Nam, G., Thomas, D., 2006: The Use of a Monte Carlo Method for Uncertainty Calculation, with an Application to the Measurement of Neutron Ambient Dose Equivalent Rate. Radiation Protection Dosimetry 121, pp. 12-23.
Cox, M.G., Eiø, C., Mana, G. and Pennecchi, F, 2006b. The generalized weighted mean of correlated quantities. Metrologia 43 S268-S275
EURACHEM/CITAC, Guide CG 4, 2000. Quantifying uncertainty in analytical measurement. Second edn., 120 S. http://www.eurachem.ul.pt/guides/QUAM2000-1.pdf.
Gavin, H. P., 2022. The Levenberg-Marquardt algorithm for nonlinear least squares curve-fitting problems. Department of Civil and Environmental Engineering, Duke University http://www.duke.edu/∼hpgavin/m-files/lm.m
Gilmore, G.: Practical Gamma-Ray Spectrometry. 2nd Edition; J. Wiley & Sons Ltd; 2008.
Hauschild, T., Jentschel, M., 2001. Comparison of maximum likelihood estimation and chi-square statistics applied to counting experiments. Nucl. Instr. & Meth A 457 (1-2), S 384-401.
Hoover, W. E., 1984: Algorithms For Confidence Circles and Ellipses. NOAA Technical Report NOS 107 C&GS 3; Charting and Geodetic Services; Rockville, MD; September 1984
http://www.ngs.noaa.gov/PUBS_LIB/AlgorithmsForConfidenceCirclesAndEllipses_TR_NOS107_CGS3.pdf
International Organisation for Standardisation, 1993. Guide to the Expression of Uncertainty in Measurement (GUM). (Geneva: ISO), corrected reprint (1995), also as ENV 13005 (1999).
International Organisation for Standardisation, 2010. Determination of the characteristic limits (decision threshold, detection limit and limits of the confidence interval) for measurements of ionizing radiation — Fundamentals and application. (Geneva: ISO), 2010.
International Organisation for Standardisation, 2019. Determination of the characteristic limits (decision threshold, detection limit and limits of the coverage interval) for measurements of ionizing radiation — Fundamentals and application. Part 1: Elementary applications (Geneva: ISO), 2019.
International Organisation for Standardisation, 2019. Determination of the characteristic limits (decision threshold, detection limit and limits of the coverage interval) for measurements of ionizing radiation — Fundamentals and application. Part 2: Advanced applications (Geneva: ISO), 2019.
International Organisation for Standardisation, 2019. Determination of the characteristic limits (decision threshold, detection limit and limits of the coverage interval) for measurements of ionizing radiation — Fundamentals and application. Part 3: Applications to unfolding methods (Geneva: ISO), 2019.
International Safety Research, Safety Support Series, 2013. Radiation Counting Statistics. Volume 1. Canada.
Janßen, H., 2004. Determination of Strontium-89 and Strontium-90 in soils and sediments. In: Quantifying uncertainty in nuclear analytical measurements, IAEA-TECDOC-1401, pp. 149-166.
JCGM 101:2008. Evaluation of measurement data — Supplement 1 to the “Guide to the expression of uncertainty in measurement” — Propagation of distributions using a Monte Carlo method GUM, Joint Committee for Guides in Metrology, 2008. (GUM Supplement 1)
JCGM 102:2011. Evaluation of measurement data – Supplement 2 to the “Guide to the expression of uncertainty in measurement” – Extension to any number of output quantities. Joint Committee for Guides in Metrology; 2011; http://www.bipm.org/en/publications/guides/gum.htm
Kacker, R.N., Datla, R.U., Parr, A.C, 2002. Combined result and associated uncertainty from interlaboratory evaluations based on the ISO Guide. Metrologia 39, 279-293.
Kacker, R.N., Datla, R.U., Parr, A.C., 2004. Statistical analysis of CIPM key comparisons based on the ISO Guide. Metrologia 41, 340-352.
Kanisch, G., 2004. Quantifying Uncertainties in the Alpha-spectrometric Analysis of Environmental Samples. In: Quantifying uncertainty in nuclear analytical measurements, IAEA-TECDOC 1401, Vienna, pp. 127-139;
Kanisch, G., 2016. Generalized evaluation of environmental radioactivity measurements with UncertRadio. Part I: Methods with linear unfolding. Applied radiation and Isotopes 110, 28–41; doi:10.1016/j.apradiso.2015.12.003
Kanisch, G., 2016. Generalized evaluation of environmental radioactivity measurements with UncertRadio. Part II: Methods without linear unfolding. Applied radiation and Isotopes 110, 74-86;
http://dx.doi.org/10.1016/j.apradiso.2015.12.003
Kessel, R., Kacker, R., Berglund, M., 2006. Coefficient of contribution to the combined standard uncertainty. Metrologia 43, S189-S195.
Knoll, G.F.. Radiation Detection and Measurement, 2nd edition, John Wiley, NewYork,1989, pp. 96-99
Laurence, T. A., Chromy, B., 2009. Efficient Levenberg-Marquardt Minimization of the Maximum Likelihood Estimator for Poisson Deviates. Report LLNL-JRNL-420247, November 13, 2009.
Marsaglia, G., Tsang, W.W., 2000. A Simple Method for Generating Gamma Variables. ACM Transactions on Mathematical Software, Vol. 26, No. 3, 363–372.
Mathews, I.P., Kouris, K., Jones, M.C., Spyrou, N.M.: Theoretical and experimental investigations on the applicability of the Poisson and Ruark-DeVol statistical density functions in the theory of radioactive decay and counting. Nucl. Instr. Meth. 171 (1979), 369-375.
Michel, R., 2000: Quality assurance of nuclear analytical techniques based on Bayesian characteristic limits. J. Radioanal. and Nucl. Chem. 245: 137-144.
Michel, R., Kirchhoff, K., 1999. Nachweis-, Erkennungs- und Vertrauensgrenzen bei Kernstrahlungsmessungen. Fachverband für Strahlenschutz e.V., Köln: TÜV-Verlag, Publikation FS-99-108-AKSIGMA, ISSN 1013-4506, 157 S.
Miller, A. Alan Miller’s Fortran Software. https://jblevins.org/mirror/amiller/
Moreno, J., Vajda, N., Burns, K., Danesi, P.R., De Regge, P., A. Fajgelj, A., 2004. Radiochemical determination of Strontium-90 in environmental samples by Liquid Scintillation Counting. In: Quantifying uncertainty in nuclear analytical measurements, IAEA-TECDOC-1401, pp. 167-193.
Pengra, D., 2008: Counting statistics of random events: A tutorial. 9 S.
http://courses.washington.edu/phys433/muon_counting/counting_stats_tutorial_b.pdf
Pishro-Nik, H., Introduction to Probability:
https://www.probabilitycourse.com/chapter11/11_1_2_basic_concepts_of_the_poisson_process.php
Pommé, S., Keightley, J., 2007. Countrate estimation of a Poisson process: unbiased fit versus central moment analysis of time interval spectra. Applied Modeling and Computations in Nuclear Science. In: Semkow, T.M., Pommé, S., Jerome, S.M., Strom, D.J. (Eds.), ACS Symposium Series 945. American Chemical Society, Washington, DC, pp.316–334.2007.ISBN0-8412-3982-7.
Press, W. H., Teukolsky, S. A., Vetterling, W. T. and Flannery, B. P., 1992. Numerical Recipes in FORTRAN, second edn. Cambridge: Cambridge Unversity Press.
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Salma, I., Zemplén-Papp, É.: Experimental investigation of statistical models describing distribution of counts. Nucl. Instr. Meth. A 312 (1992), 591-597.
Semkow, T.M.: Bayesian Inference from the Binomial and Poisson Process for Multiple Sampling. In: T.M. Semkow, S. Pommé, S.M. Jerome, D.L. Strom (Ed.): Applied Modeling and Computations in Nuclear Science. ACS Symposium Series 945, ACS, Oxford University Press, 2007.
Spyrou, N.M., Foster, J., Jones, M.C., Kouris, K., Matthews, I.P.: Should the Poisson statistical density function be used in the measurement of short-lived isotopes? J. Radioanal. Chem. 61 (1981), 121-130.
Thompson, M.A., 2015: Gaussian Statistics Lecture.
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Weise, K., Hübel, K., Michel, R., Rose, E., Schläger, M., Schrammel, D., Täschner, M., 2004. Nachweisgrenze und Erkennungsgrenze bei Kernstrahlungsmessungen: Spezielle Anwendungen. Vorschlag für eine Norm. Fachverband für Strahlenschutz e.V., Köln: TÜV-Verlag, Publikation FS-04-127-AKSIGMA, ISSN 1013-4506, 31 S.
Weise, K., Wöger, W., 1999. Meßunsicherheit und Meßdatenauswertung. Verlag Wiley-VCH Weinheim, 345 S.
Weise, K., Hübel, K., Rose, E., Schläger, M., Schrammel, D. Täschner, M., Michel, R., 2006. Bayesian decision threshold, detection limit and confidence limits in ionizing-radiation measurement. Radiat. Prot. Dosimetry 121(1), 52 – 63.
Weise, K., Kanisch, G., Michel, R., Schläger, M., Schrammel, D., Täschner, M., 2009. Monte Carlo determination of the characteristic limits in measurements of ionizing radiation – Fundamentals and numerics. Radiation Protection Dosimetry 135 (3), 169–196.
Weise, K., Kanisch, G., Michel, R., Schläger, M., Schrammel, D., Täschner, M., 2013. Characteristic values in measurements of ionizing radiation – Materials for a critical discussion on Fundamentals and alternatives. Fachverband für Strahlenschutz e.V., Köln: TÜV-Verlag, Publikation FS-2013-167-AKSIGMA, ISSN 1013-4506, 51 pp.
Wübbeler, G., Krystek, M., Elster, C., 2008. Evaluation of measurement uncertainty and its numerical calculation by a Monte Carlo method. Meas. Sci. Technol. 19, 084009 (4pp)