Bayesian Data-Analysis Toolbox
Release 4.23, Manual Version 3
G. Larry BretthorstBiomedical MR Laboratory
Washington University School Of Medicine,Campus Box 8227
Room 2313, East Bldg.,4525 Scott Ave.
St. Louis MO 63110http://bayes.wustl.edu
Email: [email protected]
September 18, 2018
Bibliography
[1] Rev. Thomas Bayes (1763), “An Essay Toward Solving a Problem in the Doctrine of Chances,”Philos. Trans. R. Soc. London, 53, pp. 370-418; reprinted in Biometrika, 45, pp. 293-315 (1958),and Facsimiles of Two Papers by Bayes, with commentary by W. Edwards Deming, New York,Hafner, 1963.
[2] G. Larry Bretthorst (1988), “Bayesian Spectrum Analysis and Parameter Estimation,” in Lec-ture Notes in Statistics, 48, J. Berger, S. Fienberg, J. Gani, K. Krickenberg, and B. Singer(eds), Springer-Verlag, New York, New York.
[3] G. Larry Bretthorst (1990), “An Introduction to Parameter Estimation Using Bayesian Prob-ability Theory,” in Maximum Entropy and Bayesian Methods, Dartmouth College 1989, P.Fougere ed., pp. 53-79, Kluwer Academic Publishers, Dordrecht the Netherlands.
[4] G. Larry Bretthorst (1990), “Bayesian Analysis I. Parameter Estimation Using QuadratureNMR Models” J. Magn. Reson., 88, pp. 533-551.
[5] G. Larry Bretthorst (1990), “Bayesian Analysis II. Signal Detection And Model Selection” J.Magn. Reson., 88, pp. 552-570.
[6] G. Larry Bretthorst (1990), “Bayesian Analysis III. Examples Relevant to NMR” J. Magn.Reson., 88, pp. 571-595.
[7] G. Larry Bretthorst (1991), “Bayesian Analysis. IV. Noise and Computing Time Considera-tions,” J. Magn. Reson., 93, pp. 369-394.
[8] G. Larry Bretthorst (1992), “Bayesian Analysis. V. Amplitude Estimation for Multiple Well-Separated Sinusoids,” J. Magn. Reson., 98, pp. 501-523.
[9] G. Larry Bretthorst (1992), “Estimating The Ratio Of Two Amplitudes In Nuclear MagneticResonance Data,” in Maximum Entropy and Bayesian Methods, C. R. Smith et al. (eds.),pp. 67-77, Kluwer Academic Publishers, the Netherlands.
[10] G. Larry Bretthorst (1993), “On The Difference In Means,” in Physics & Probability Essays inhonor of Edwin T. Jaynes, W. T. Grandy and P. W. Milonni (eds.), pp. 177-194, CambridgeUniversity Press, England.
[11] G. Larry Bretthorst (1996), “An Introduction To Model Selection Using Bayesian ProbabilityTheory,” in Maximum Entropy and Bayesian Methods, G. R. Heidbreder, ed., pp. 1-42, KluwerAcademic Publishers, Printed in the Netherlands.
479
480 BIBLIOGRAPHY
[12] G. Larry Bretthorst (1999), “The Near-Irrelevance of Sampling Frequency Distributions,” inMaximum Entropy and Bayesian Methods, W. von der Linden et al. (eds.), pp. 21-46, KluwerAcademic Publishers, the Netherlands.
[13] G. Larry Bretthorst (2001), “Nonuniform Sampling: Bandwidth and Aliasing,” in MaximumEntropy and Bayesian Methods in Science and Engineering, Joshua Rychert, Gary Ericksonand C. Ray Smith eds., pp. 1-28, American Institute of Physics, USA.
[14] G. Larry Bretthorst, Christopher D. Kroenke, and Jeffrey J. Neil (2004), “Characterizing WaterDiffusion In Fixed Baboon Brain,” in Bayesian Inference And Maximum Entropy Methods InScience And Engineering, Rainer Fischer, Roland Preuss and Udo von Toussaint eds., AIPconference Proceedings, 735, pp. 3-15.
[15] G. Larry Bretthorst, William C. Hutton, Joel R. Garbow, and Joseph J.H. Ackerman (2005),“Exponential parameter estimation (in NMR) using Bayesian probability theory,” Concepts inMagnetic Resonance, 27A, Issue 2, pp. 55-63.
[16] G. Larry Bretthorst, William C. Hutton, Joel R. Garbow, and Joseph J. H. Ackerman (2005),“Exponential model selection (in NMR) using Bayesian probability theory,” Concepts in Mag-netic Resonance, 27A, Issue 2, pp. 64-72.
[17] G. Larry Bretthorst, William C. Hutton, Joel R. Garbow, and Joseph J.H. Ackerman (2005),“How accurately can parameters from exponential models be estimated? A Bayesian view,”Concepts in Magnetic Resonance, 27A, Issue 2, pp. 73-83.
[18] G. Larry Bretthorst, W. C. Hutton, J. R. Garbow, and Joseph J. H. Ackerman (2008), “HighDynamic Range MRS Time-Domain Signal Analysis,” Magn. Reson. in Med., 62, pp. 1026-1035.
[19] V. Chandramouli, K. Ekberg, W. C. Schumann, S. C. Kalhan, J. Wahren, and B. R. Landau(1997), “Quantifying gluconeogenesis during fasting,” American Journal of Physiology, 273,pp. H1209-H1215.
[20] R. T. Cox (1961), “The Algebra of Probable Inference,” Johns Hopkins Univ. Press, Baltimore.
[21] Andre d’Avignon, G. Larry Bretthorst, Marilyn Emerson Holtzer, and Alfred Holtzer (1998),“Site-Specific Thermodynamics and Kinetics of a Coiled-Coil Transition by Spin InversionTransfer NMR,” Biophysical Journal, 74, pp. 3190-3197.
[22] Andre d’Avignon, G. Larry Bretthorst, Marilyn Emerson Holtzer, and Alfred Holtzer (1999),“Thermodynamics and Kinetics of a Folded-Folded Transition at Valine-9 of a GCN4-LikeLeucine Zipper,” Biophysical Journal, 76, pp. 2752-2759.
[23] David Freedman, and Persi Diaconis (1981), “On the histogram as a density estimator: L2
theory,” Zeitschrift f¨r Wahrscheinlichkeitstheorie und verwandte Gebiete, 57, 4, pp. 453-476.
[24] W. R. Gilks, S. Richardson, and D. J. Spiegelhalter (1996), “Markov Chain Monte Carlo inPractice,” Chapman & Hall, London.
BIBLIOGRAPHY 481
[25] Paul M. Goggans, and Ying Chi (2004), “Using Thermodynamic Integration to Calculate thePosterior Probability in Bayesian Model Selection Problems,” in Bayesian Inference and Maxi-mum Entropy Methods in Science and Engineering: 23rd International Workshop, 707, pp. 59-66.
[26] Marilyn Emerson Holtzer, G. Larry Bretthorst, D. Andre d’Avignon, Ruth Hogue Angelette,Lisa Mints, and Alfred Holtzer (2001), “Temperature Dependence of the Folding and UnfoldingKinetics of the GCN4 Leucine Lipper via 13C alpha-NMR,” Biophysical Journal, 80, pp. 939-951.
[27] E. T. Jaynes (1968), “Prior Probabilities,” IEEE Transactions on Systems Science and Cyber-netics, SSC-4, pp. 227-241; reprinted in [30].
[28] E. T. Jaynes (1978), “Where Do We Stand On Maximum Entropy?” in The Maximum EntropyFormalism, R. D. Levine and M. Tribus Eds., pp. 15-118, Cambridge: MIT Press, Reprintedin [30].
[29] E. T. Jaynes (1980), “Marginalization and Prior Probabilities,” in Bayesian Analysis inEconometrics and Statistics, A. Zellner ed., North-Holland Publishing Company, Amsterdam;reprinted in [30].
[30] E. T. Jaynes (1983), “Papers on Probability, Statistics and Statistical Physics,” a reprint col-lection, D. Reidel, Dordrecht the Netherlands; second edition Kluwer Academic Publishers,Dordrecht the Netherlands, 1989.
[31] E. T. Jaynes (1957), “How Does the Brain do Plausible Reasoning?” unpublished StanfordUniversity Microwave Laboratory Report No. 421; reprinted in Maximum-Entropy and BayesianMethods in Science and Engineering 1, pp. 1-24, G. J. Erickson and C. R. Smith Eds., 1988.
[32] E. T. Jaynes (2003), “Probability Theory—The Logic of Science,” edited by G. Larry Bretthorst,Cambridge University Press, Cambridge UK.
[33] Sir Harold Jeffreys (1939), “Theory of Probability,” Oxford Univ. Press, London; Later editions,1948, 1961.
[34] John G. Jones, Michael A. Solomon, Suzanne M. Cole, A. Dean Sherry, and Craig R. Mal-loy (2001) “An integrated 2H and 13C NMR study of gluconeogenesis and TCA cycle flux inhumans,” American Journal of Physiology, Endocrinology, and Metabolism, 281, pp. H848-H856.
[35] John Kotyk, N. G. Hoffman, W. C. Hutton, G. Larry Bretthorst, and J. J. H. Ackerman (1992),“Comparison of Fourier and Bayesian Analysis of NMR Signals. I. Well-Separated Resonances(The Single-Frequency Case),” J. Magn. Reson., 98, pp. 483–500.
[36] Pierre Simon Laplace (1814), “A Philosophical Essay on Probabilities,” John Wiley & Sons,London, Chapman & Hall, Limited 1902. Translated from the 6th edition by F. W. Truscottand F. L. Emory.
[37] N. Lartillot, and H. Philippe (2006), “Computing Bayes Factors Using Thermodynamic Inte-gration,” Systematic Biology, 55 (2), pp. 195-207.
482 BIBLIOGRAPHY
[38] D. Le Bihan, and E. Breton (1985), “Imagerie de diffusion in-vivo par rsonance,” Comptesrendus de l’Acadmie des Sciences (Paris), 301 (15), pp. 1109-1112.
[39] N. R. Lomb (1976), “Least-Squares Frequency Analysis of Unevenly Spaced Data,” Astrophys-ical and Space Science, 39, pp. 447-462.
[40] T. J. Loredo (1990), “From Laplace To SN 1987A: Bayesian Inference In Astrophysics,” inMaximum Entropy and Bayesian Methods, P. F. Fougere (ed), Kluwer Academic Publishers,Dordrecht, The Netherlands.
[41] Craig R. Malloy, A. Dean Sherry, and Mark Jeffrey (1988), “Evaluation of Carbon Flux andSubstrate Selection through Alternate Pathways Involving the Citric Acid Cycle of the Heartby 13C NMR Spectroscopy,” Journal of Biological Chemistry, 263 (15), pp. 6964-6971.
[42] Craig R. Malloy, Dean Sherry, and Mark Jeffrey (1990), “Analysis of tricarboxylic acid cycle ofthe heart using 13C isotope isomers,” American Journal of Physiology, 259, pp. H987-H995.
[43] Lawrence R. Mead and Nikos Papanicolaou, “Maximum entropy in the problem of moments,”J. Math. Phys. 25, 2404–2417 (1984).
[44] K. Merboldt, Wolfgang Hanicke, and Jens Frahm (1969), “Self-diffusion NMR imaging usingstimulated echoes,” Journal of Magnetic Resonance, 64 (3), pp. 479-486.
[45] Nicholas Metropolis, Arianna W. Rosenbluth, Marshall N. Rosenbluth, Augusta H. Teller, andEdward Teller (1953), “Equation of State Calculations by Fast Computing Machines,” Journalof Chemical Physics. The previous link is to the Americain Institute of Physics and if you donot have access to Science Sitations you many not be able to retrieve this paper.
[46] Radford M. Neal (1993), “Probabilistic Inference Using Markov Chain Monte Carlo Methods,”technical report CRG-TR-93-1, Dept. of Computer Science, University of Toronto.
[47] Jeffrey J. Neil, and G. Larry Bretthorst (1993), “On the Use of Bayesian Probability Theory forAnalysis of Exponential Decay Data: An Example Taken from Intravoxel Incoherent MotionExperiments,” Magn. Reson. in Med., 29, pp. 642–647.
[48] H. Nyquist (1924), “Certain Factors Affecting Telegraph Speed,” Bell System Technical Journal,3, pp. 324-346.
[49] H. Nyquist (1928), “Certain Topics in Telegraph Transmission Theory,” Transactions AIEE, 3,pp. 617-644.
[50] William H. Press, Saul A. Teukolsky, William T. Vetterling and Brian P. Flannery (1992),“Numerical Recipes The Art of Scientific Computing Second Edition,” Cambridge UniversityPress, Cambridge UK.
[51] Emanuel Parzen (1962), “On Estimation of a Probability Density Function and Mode,” Annalsof Mathematical Statistics 33, 1065–1076
[52] Karl Pearson (1895), “Contributions to the Mathematical Theory of Evolution. II. Skew Vari-ation in Homogeneous Material,” Phil. Trans. R. Soc. A 186, 343–326.
BIBLIOGRAPHY 483
[53] Murray Rosenblatt, “Remarks on Some Nonparametric Estimates of a Density Function,” An-nals of Mathematical Statistics 27, 832–837 (1956).
[54] Jeffery D. Scargle (1981), “Studies in Astronomical Time Series Analysis I. Random Process InThe Time Domain,” Astrophysical Journal Supplement Series, 45, pp. 1-71.
[55] Jeffery D. Scargle (1982), “Studies in Astronomical Time Series Analysis II. Statistical Aspectsof Spectral Analysis of Unevenly Sampled Data,” Astrophysical Journal, 263, pp. 835-853.
[56] Jeffery D. Scargle (1989), “Studies in Astronomical Time Series Analysis. III. Fourier Trans-forms, Autocorrelation Functions, and Cross-correlation Functions of Unevenly Spaced Data,”Astrophysical Journal, 343, pp. 874-887.
[57] Arthur Schuster (1905), “The Periodogram and its Optical Analogy,” Proceedings of the RoyalSociety of London, 77, p. 136-140.
[58] Claude E. Shannon (1948), “A Mathematical Theory of Communication,” Bell Syst. Tech. J.,27, pp. 379-423.
[59] John E. Shore, and Rodney W. Johnson (1981), ”Properties of cross-entropy minimization,”IEEE Trans. on Information Theory, IT-27, No. 4, pp. 472-482.
[60] John E. Shore and Rodney W. Johnson (1980), “Axiomatic derivation of the principle of maxi-mum entropy and the principle of minimum cross-entropy,” IEEE Trans. on Information The-ory, IT-26 (1), pp. 26-37.
[61] Devinderjit Sivia, and John Skilling (2006), “Data Analysis: A Bayesian Tutorial,” OxfordUniversity Press, USA.
[62] Edward O. Stejskal and Tanner, J. E. (1965), “Spin Diffusion Measurements: Spin Echoesin the Presence of a Time-Dependent Field Gradient.” Journal of Chemical Physics, 42 (1),pp. 288-292.
[63] D. G. Taylor and Bushell, M. C. (1985), “The spatial mapping of translational diffusion coeffi-cients by the NMR imaging technique,” Physics in Medicine and Biology, 30 (4), pp. 345-349.
[64] Myron Tribus (1969), “Rational Descriptions, Decisions and Designs,” Pergamon Press, Oxford.
[65] P. M. Woodward (1953), “Probability and Information Theory, with Applications to Radar,”McGraw-Hill, N. Y. Second edition (1987); R. E. Krieger Pub. Co., Malabar, Florida.
[66] Arnold Zellner (1971), “An Introduction to Bayesian Inference in Econometrics,” John Wileyand Sons, New York.
Index
Ak definition, 349Hj`(ti) definition, 349λ` definition, 349gjk eigenvalue, 349
Abscissa, 437Computational, 436Generating, 427Loading, 39Multicolumn, 437Number Of Columns, 458Total Data Values, 456
Aliases, 113, 126Amplitudes orthonormal definition, 349Analyze Image Pixel Package, 411
Modification History, 413Phased Images, 397Reports
Bayes Accepted, 413Using, 413Viewers
Fortran/C Models, 411Image, 411Prior Probabilities, 413
WidgetsAbscissa File, 411Build, 411Find Outliers, 411Get Statistics, 413System, 411User, 411
Analyze Image Pixel Unique Package, 423Highlight
Abscissa, 425Data, 425
Input ImageAbscissa, 423
Data, 423Reports
Bayes Accepted, 425Console Log, 425McMC Values, 425
Using, 425Viewers
Fortran/C Models, 423Image, 423Prior Probabilities, 425
WidgetsBuild, 423Find Outliers, 423Get Statistics, 425System, 423User, 423
Ascii Data Viewer, 53Assigning Probabilities, 118
Bandwidth, 111, 127Bayes Analyze Package, 155
Levenberg-Marquardt , 171Step, 194
Algorithm, 175Amplitudes, 197, 198Bayes Model, 159, 161Bayesian Calculations, 167Bruker, 162Build BA Model, 159Covariance, 174Default Parameters Settings, 155Error Messages, 200Fid Model Viewer, 160Interface, 156Likelihood
Gaussian, 158Student’s t-distribution, 158
484
INDEX 485
Log File, 193, 195Lorentzian lineshape, 161Marking Resonances, 157ModelJo, 165Jp, 165Js, 165Amplitude, 163, 164Bessel Function, 163Constants Models, 157Correlated, 157, 162, 164Equation, 161, 164, 164First Order Phase, 157, 162, 164First Point, 162, 164Gaussian, 163Imaginary Constant, 164Multi-Exponential, 163Multiple Data Sets, 165Multiplet Order, 164Multiplet Orders, 164Multiplets, 162Multiplets of Multiplets, 164Non-Lorentzian, 163Offsets, 162Real Constant, 164Relative Amplitude, 164–166Resonance Frequency, 165Shim Order, 163Shimming, 166Shimming Order, 164Uncorrelated, 157, 162, 164Zero Order Phase, 157, 162, 164
Model Interface, 160Multiplets, 158Newton-Raphson, 171Noise File, 158Noise Standard Deviation, 158Outputs
Bayes.accepted File, 177bayes.log.nnnn File, 177, 193, 193bayes.model.nnnn File, 177, 185, 197, 197bayes.noise File, 180bayes.noise.nnnn File, 158, 180bayes.output.nnnn File, 176, 186, 186bayes.params File, 176, 177bayes.params.nnnn File, 176, 177, 177
bayes.probabilities.nnnn File, 177, 190, 190bayes.status.nnnn File, 177, 196, 200bayes.summary1.nnnn File, 177, 198, 198bayes.summary2.nnnn File, 177, 199, 199bayes.summary3.nnnn File, 177, 200, 200Global Parameters, 182, 183Model File, 184Probabilities file, 191Zero Order Phase, 182
Parameter FileActivate Shims, 180Analysis Directory, 178By Fid, 181Data Type, 180Default Model, 181Directory Organization, 180Fid Model Name, 178File Version, 178First Fid, 181First Order Phase, 180, 183Imaginary Constant, 184Last Fid, 181lb, 182Maximum Candidates, 182Maximum New Resonances, 182Model Fid Number, 181Model Name, 184Model Names, 181Model Number, 184Model Points, 181Multiplets of Multiplets, 185Noise Start, 181Numerical Parameters, 178Output Format, 180Prior Odds, 182Procpar, 178Real Constant, 184Relative Amplitude, 183Resonance Model, 185Shim Order, 182Spectrometer Frequency, 182Text Parameters, 178Total Complex Data Values, 181Total Data Values, 181Total Sampling Time, 182True Reference, 182
486 INDEX
Units, 180Use Noise StdDev, 180User Reference, 182
Prior Probabilities, 167Probabilities File, 191Product Rule, 168Relative Amplitude, 167Remove Resonances, 159Reports
Bayes Status, 155Save/Reset, 159Search, 166
Levenberg-Marquardt , 166Short Parameter Description, 195Siemens, 162Status File, 196Steepest Descents, 173Sum Rule, 168Summary File, 198Summary Reports, 176Summary2, 199Summary3, 201Units, 161Using, 157Varian/Agilent, 162Widgets, 155
By, 158, 176First Point, 157, 163From, 158, 176Imag Offset, 163Imaginary Offset, 157Mark, 159Max New Res, 157New, 159Noise, 158Phase, 157Primary, 158Real Offset, 157, 163Remove, 159Remove All, 159Reset, 159, 193Restore, 159Save, 159Secondary, 159Shim Order, 157, 163Signal, 158
To, 158, 176Bayes Find Resonances Package, 239
Bayesian Calculations, 241Current Fid, 239Model Equation, 241Number of data sets, 239Phase Model
Automatic, 239, 242Common, 239, 242Independent, 239, 242
Prior Probabilities, 243–245Reports
Bayes Accepted, 241, 246Condensed, 246Console log, 246McMC Values, 246Prob Model, 246
Using, 239, 241Viewers
Fid Data, 240Fid Model, 240, 246File, 246Plot Results, 246Text, 246
WidgetsBuild FID Model, 240, 241, 246Constant, 239, 242First Trace, 239Last Trace, 239Model Fid Number, 241Phase Model, 239, 242
Bayes Home Directory, 45, 49Bayes Manual pdf, 469Bayes Metabolite Package
WidgetsShift Left, 222Shift Right, 222
Bayes Metabolite Package, 219Aligning Resonances, 221Bayesian Calculation, 225Metabolite Locations, 221Model Equation, 223Reports
Bayes Accepted, 221, 238Condensed, 238Console log, 238
INDEX 487
McMC Values, 238Prob Model, 238
ViewersFid Data, 219Fid Model, 221, 236File, 222, 238Metabolite, 221Plot Results, 238Text, 238
WidgetsFid Model, 221Fid Model Viewer, 221Load System Metabolite File, 219Load System Resonance File, 221Load User Metabolite File, 219Load User Resonance File, 221Shift Left, 221Shift Right, 221
Bayes Model, 159, 159Bayes Test Data Package, 427
Parameters, 431Reports
Bayes Accepted, 428Condensed, 429McMC Values, 429, 431–433
ViewersFortran/C Models, 427Image, 428Prior Probabilities, 427Text Data, 430Text Results, 429
Widgets# Images, 427# Slices, 427Abscissa, 427ArrayDim, 427Build, 427Get Job, 428Max Value, 427Noise SD, 427Parameter Ranges, 428Pe, 427Ro, 427Run, 428Set (server), 428Status, 428
Bayes’ Theorem, 100, 139, 145, 153, 167, 211,226, 243, 252, 261, 269, 278, 288, 295,306, 314, 315, 317, 318, 331, 333, 343,370, 399, 407, 439
Bayes.acceptedBody, 77Header, 76
Behrens-Fisher Package, 311Bayesian Calculations
Derived Probabilities, 320Different Mean And Same Variance, 318Different Mean And Variance, 319Parameter Estimation, 321Same Mean And Different Variance, 317Same Mean And Variance, 315
Model EquationDifferent Mean And Same Variance, 318Different Mean And Variance, 319Same Mean And Different Variance, 317Same Mean And Variance, 315
Number of data sets, 311Parameter Listing, 323Prior Probabilities
Different Mean And Same Variance, 318Different Mean And Variance, 319Same Mean And Different Variance, 317Same Means And Same Variance, 315
ReportsBayes Accepted, 311, 322Condensed, 322Console Log, 322, 323McMC Values, 322, 323Prob Model, 322
Using, 311Viewers
File, 322Plot Results, 322, 324Prior Probabilities, 311Text, 322
WidgetsNone, 311
Big Endian, 471, 473Big Magnetization Transfer Package, 259
Bayesian Calculations, 259Files
Bayes Analyze, 264
488 INDEX
Fid, 263Peak Pick, 262
Model Equation, 261Number of data sets, 259Prior Probabilities, 261Reports
Bayes Accepted, 259, 262Condensed, 262Console log, 262McMC Values, 262Prob Model, 262
Using, 259Viewers
Ascii Data, 259File, 262Prior Probabilities, 259Text, 262
WidgetsFind Outliers, 259
Big Peak/Little Peak Package, 207Bayesian Calculations, 209Fid Analyzed, 207Model Equation, 210
Metabolites, 209Solvent, 210
Number of data sets, 207Prior Probabilities
Metabolite, 207Solvent, 207
Removing Resonances, 207Reports
Bayes Accepted, 209, 216Condensed, 216Console log, 216McMC Values, 216Prob Model, 216
Using, 207Viewers
File, 216Model, 209Plot Results, 216Prior Probabilities, 207Text, 216
WidgetsMetabolite, 207Solvent, 207
Binned Density Function Estimation, 355Binned Histogram Package
ReportsBayes Accepted, 357
ViewersAscii, 355
Binned Histograms PackageUsing, 357Viewers
Prior Probabilities, 355Bloch-McConnell Equations, 267, 277
Changing the Bayes Home Directory, 469Compilers, 29
CC, 29, 455Fortran, 29, 455
Correlations, 91
Diffusion Tensor Package, 247Ascii File Formats, 247, 254, 255Bayesian Calculations, 249Prior Probabilities
∆, 254Γ, 254δ, 254σ, 253Amplitudes, 253Eigenvalues, 253Euler Angles, 253Likelihood, 253Parameter, 254
ReportsBayes Accepted, 247, 255Condensed, 255Console log, 255McMC Values, 255Prob Model, 255
Symmetries, 253Using, 247Viewers
File, 247, 255Plot Results, 255Prior Probabilities, 247, 253Text, 255
WidgetsAbscissa Options, 248
INDEX 489
Find Outliers, 247Include Constant, 247, 248, 255Tensor Number, 247, 248, 255Use b Matrix, 255Use b Vectors, 255Use g Vectors, 254
Discrete Fourier Transform, 110, 113, 123
Enter Ascii Model Package, 329Bayesian Calculations, 332
Marginalization, 332No Marginalization, 331
Fortran/C Models, 330, 335Model Equation
Marginalization, 331No Marginalization, 331
Output NamesDerived, 335Parameters, 335
ReportsBayes Accepted, 331, 335Bayes Params, 335Condensed, 335Console log, 335McMC Values, 335Prob Model, 335
Using, 331Viewers
Ascii Data, 329File, 335Fortran/C Models, 329Plot Results, 335Prior Probabilities, 329Text, 335
WidgetsBuild, 329Find Outliers, 329System, 329User, 329
Enter Ascii Model Selection Package, 341Bayesian Calculations
Marginalization, 346No Marginalization, 344
Fortran/C Models, 341, 343, 353Model Equation, 343
No Marginalization, 343
With Marginalization, 347Output Names
Derived, 354Parameters, 353
ReportsBayes Accepted, 343, 353Condensed, 353Console log, 353McMC Values, 353Params File, 353Prob Model, 353
Using, 343Viewers
Ascii Data, 341File, 353Fortran/C Models, 341Plot Results, 353Prior Probabilities Not Used, 341Text, 353
WidgetsBuild Not Used, 341Find Outliers, 341System, 341User, 341
Errors In Variables Package, 303Ascii File Formats
Errors In X and Y Known, 303, 309Errors In X Known, 303, 309Errors In Y Known, 303, 309Errors Unknown, 303, 309
Bayesian Calculations, 305Data Error Bars, 303Files
Ascii, 303Bayes Analyze, 303Peak Pick, 303
Model Equation, 305Number of data sets, 303Reports
Bayes Accepted, 305, 309Condensed, 309Console log, 309McMC Values, 309Prob Model, 309
Using, 305Viewers
490 INDEX
Ascii Data, 303File, 309Plot Results, 309Text, 309
WidgetsGiven Errors In, 303Order, 303
ExponentialsGiven Package, 137Inversion Recovery Package, 151Magnetization Transfer Package, 267Unknown Number of Package, 143
Fid Data Viewer, 53Fid Model Viewer, 68File Format
Ascii, 436File Viewer, 80Files
4dfp, 59, 428, 430, 470, 471Header, 473Reading, 471
Abscissa, 39, 77, 470afh, 53ASCII, 35, 36Ascii, 53, 54, 435k-space, 437Abscissa, 435, 436, 437Data, 435Image, 436
Bayes Analyze, 36Bayes.accepted, 51, 76Bayes.params, 76, 79Bayes.prob.model, 447BayesManual.pdf, 469Condensed, 77, 78Console.log, 76, 79, 465dir.info, 470fid, 470, 470
ASCII, 36ffh, 56Model, 68, 70procpar, 470Siemens Raw, 36Siemens Rda, 36Spectroscopic, 53
Varian fid, 36Fortran/C Models, 42, 455, 457, 458, 465–
467Images
4dfp, 38Binary, 38Bruker 2dseq, 38Bruker stack, 38DICOM, 38FDF, 38Multi-Column Text, 38Siemens IMA, 38
k-spaceText, 36Varian fid, 36
mcmc.values, 76, 449Model Listing, 77prob.model, 76procpar, 470Raw, 36RDA, 36Statistics, 65System.err.txt, 469System.out.txt, 469Varian fid, 36WaterViscosityTable, 469
Fortran/C Model Viewer, 93Popup Editor, 93
Fortran/C Models, 42, 330, 335, 353, 455Abscissa, 463Body, 463
Abscissa, 457Declarations, 462Derived Parameters, 457, 459, 463Edit/Create New Model, 42, 455I/O, 464Marginalization, 464Gj(Ω, ti), 464Amplitude Range, 465Example, 465, 466Model Vectors, 465Ordering Amplitudes, 465Parameter File, 465, 467Parameter Order, 465Parameters, 465
Model Files, 455
INDEX 491
Model Selection, 464No Marginalization, 457S(ti), 455Example, 456
Parameter File, 458, 459, 465Parameters, 463Signal, 463Subroutine Interface, 460
Abscissa, 462Current Set, 460Derived Parameters, 461Maximum No Of Data Values, 461Number Of Abscissa Columns, 461Number Of Data Columns, 461Number Of Derived Parameters, 461Number Of Model Vectors, 461Number Of Parameters, 460Parameters, 461Signal, 462Total Complex Data Values, 461
Subroutines and Functions, 464Frequency Estimation, 114, 132
Given Exponential Package, 137Bayesian Calculations, 140Files
Ascii, 137Bayes Analyze, 137Peak Pick, 137
Model Equation, 139Number of data sets, 139Prior Probabilities, 139–141Reports
Bayes Accepted, 137, 141Condensed, 141Console log, 141McMC Values, 141Prob Model, 141
Symmetries, 141, 148Using, 137Viewers
File, 141Plot Results, 141Prior Probabilities, 137, 139Text, 141
Widgets
Constant, 137, 139Find Outliers, 137Given Order, 27Include Constant, 27Order, 137, 139
Given Polynomial Order Package, 285Bayesian Calculations, 288Files
Ascii, 285Bayes Analyze, 285Peak Pick, 285
Gram-Schmidt, 287Model Equation, 287Number of data sets, 285Prior Probabilities, 289Reports
Bayes Accepted, 285, 291Condensed, 291Console log, 291McMC Values, 291Prob Model, 291
Scatter Plots, 292Using, 285Viewers
File, 290Plot Results, 291Text, 290
WidgetsSet Order, 285
HistogramsBinned, 381Kernel Density, 381
Image Model Selection Package, 415Abscissa, 415Fortran/C Models, 415, 417Reports
Bayes Accepted, 417Using, 417Viewers
Fortran/C Models, 415Image, 415
WidgetsNoise SD, 415System, 415
492 INDEX
Use Gaussian, 415User, 415
Image Viewer, 59Images
FlipHorizontal, 63Vertical, 63
Grayscale, 63ImageJ, 63Original, 63
Inversion Recovery Package, 151Bayesian Calculations, 153Model Equation, 153Number of data sets, 153Prior Probabilities, 153Reports
Bayes Accepted, 151, 154Condensed, 154Console Log, 154McMC Values, 154Prob Model, 154
Using, 151Viewers
Plot Results, 154Prior Probability, 151
WidgetsFind Outliers, 151
Kernel Density Function Package, 361Ascii File Format, 361Bayesian Calculations, 369Data Requirements, 361Data, Model And Residuals, 369Kernels, 369
Biweight, 362Cosine, 362Epanechnikov, 362Exponential, 362Gaussian, 362, 370nonnegative, 361Real Valued, 361Triangular, 362Tricube, 362Triweight, 362Uniform, 362
Likelihood, 371
Number of data sets, 364Plots
Expected Density Function, 367, 368Mean Density Function, 367, 368Posterior Probability for the Kernel Type,
365Posterior Probability for the Number Of
Kernels, 366Scatter Plots of Model Averaged Density
Function, 368Standard Deviation of the Mean Density
Function, 367, 368Prior Probabilities
Kernel Center, 371Kernel Smoothing Parameter, 371Kernel Type, 370Number Of Kernels, 370
ReportsBayes Accepted, 364Condensed, 372McMC Values, 372Prob Model, 372
Using, 364Viewers
Ascii, 361Widgets
Kernel Type, 364Output Size, 364
Levenberg-Marquardt, 171Linear Phasing Package, 395, 409
Interface, 397Model Equation, 398Widgets
cf, 403Display, 403Display Array Element, 403fn, 403fn1, 403Image Type, 402Load An Image, 402np, 403nv, 403Process, 403
Load Working Directory, 33Logical Independence, 117
INDEX 493
Magnetization Transfer Kinetics Package, 275Arrhenius Plot, 281Bayesian Calculation, 278Boltzmann’s Constant, 277Eyring Equation, 275, 276, 277, 280Model Equation, 277Plank’s Constant, 277Prior Probabilities, 279Reports
Bayes Accepted, 277, 281Condensed, 281Console log, 281McMC Values, 281Prob Model, 281
Sum and Difference Variables, 280Transmission coefficient, 277Universal Gas Constant, 277Using, 277van’t Hoff Plot, 281Viewers
Ascii File, 275File, 281Prior Probabilities, 275Text, 281
WidgetsLoad, 275, 281Set, 275Uncertainty, 275
Magnetization Transfer Package, 265Bayesian Calculations, 267Files
Ascii, 265Bayes Analyze, 265Inversion Recovery, 272Peak Pick, 265
Model Equation, 267Number of data sets, 265Prior Probabilities, 265, 270Reports
Bayes Accepted, 267, 272Condensed, 272Console log, 272McMC Values, 272Prob Model, 272
Three Column Data, 265Using, 267
ViewersAscii Data, 265Fid Data, 272File, 271Plot Results, 262, 272, 281Prior Probabilities, 265Text, 271
WidgetsFind Outliers, 265
Marginalization, 100Bayes Analyze Package, 174Behrens-Fisher, 315Big Magnetization Transfer, 261Big Peak/Little Peak, 211Diffusion Tensors, 252Enter Ascii Model Package, 331Errors In Variables, 306Fortran/C Models, 464Given Exponential, 139Inversion Recovery, 153Linear Phasing, 399Magnetization Transfer, 269Magnetization Transfer Kinetics, 278Metabolic Analysis, 225Nonexhaustive Hypotheses, 101Nuisance Hypotheses, 100Nuisance Parameter, 100Unknown Number of Exponentials, 146
Markov chain Monte Carlo, 132, 439Acceptance Rate, 444Annealing Schedule, 91, 442
Dynamic, 443Linear, 442
Killing Simulations, 443Maximum Posterior Probability, 91Metropolis-Hastings, 439Mixing, 91Monte Carlo Integration, 440Multiple Simulations, 441Posterior Probability, 440Random Number Generators, 440Repeats, 91Sampling, 91Simulated Annealing, 442the Proposal, 444
494 INDEX
MaxEnt Density Function Estimation Package,373
Data Requirements, 381Plots
Contour/Scatter, 375, 379Number Of Multipliers, 375, 378
ReportsBayes Accepted, 375Console Log, 375
Using, 375Viewers
Ascii, 373Plot, 375, 378Prior Probabilities, 373
WidgetsHistogram Size, 373Order, 373
Maximum Entropy Method Of Moments, 102,377, 381
Advantages, 386Problems, 386Review, 381
Maximum Entropy Method Of Moments PackageBayesian Calculations, 387Plots
Data, Model and Residuals, 380Menus
Files, 24, 354dfp, 37, 38Abscissa, 35, 39ASCII, 35, 36Binary, 38Bruker, 37Bruker 2dseq, 38Bruker Stack, 38DICOM, 37, 38FDF, 37, 38fid, 36, 37General Binary, 37Images, 35Import Working Directories in Batch, 40Import Working Directory, 40Load Images, 36, 37, 59Load Working Directory, 35Multi-Column Text, 37, 38Save Working Directory, 35, 39
Siemens IMA, 37, 38Single-Column Text, 38Spectroscopic Fid, 35Test Data, 35, 39Text k-space, 36Text k-space fid, 37User Manual, 35, 39
Help, 24Packages, 22, 24, 33, 40Settings, 46
Add Server, 48Auto Configure Server, 48McMC Parameters, 24, 46, 48Min Annealing Steps, 48, 48Port number, 48Preferences, 49, 63Remove Server, 48, 49Repetitions, 46, 48Server Name, 48Server Setup, 24, 26, 48Set Window Size, 49Simulations, 46, 48View Server Installation Info, 48, 49
Spectroscopy fid, 36Utilities, 24, 50
Memory Monitor, 50Software Updates, 50System Information, 50
WorkDirCreating, 22, 33, 46Deleting, 22, 33, 46List, 24, 46Loading, 46Name, 46Popup, 47
Model ComparisonBig Peak/Little Peak Package, 211
model orthonormal definition, 349Mouse
Control-left, 59Fid Data Viewer
Left, 56Right, 56
Shift-left, 59Multiplets
J-Coupling
INDEX 495
Center, 159Primary, 159Secondary, 159
Newton-Raphson, 171Noise Standard Deviation, 64Non-Linear Phasing Package, 405
Calculations, 407Model Equation, 405, 407Widgets
Process, 409Write Ascii images, 409Write imaginary images, 409
Nuisance Parameter, 100, 115, 135Nyquist Critical Frequency, 111, 127
orthonormal, 349Outliers, 475
Mean Parameter, 477Model, 475Prob Number of, 476Proposal, 475Red dot, 477Weighted Average, 477
PackagesAnalyze Image Pixel Unique, 423Bayes Analyze, 20, 43, 57, 155, 200Bayes Find Resonances, 21, 239Bayes Test Data, 427Behrens-Fisher, 21, 44, 311Big Magnetization Transfer, 20, 43, 259Big Peak/Little Peak, 20, 43, 207Binned Density Function Estimation, 355Binned Histograms, 21, 44Diffusion Tensors, 20, 40, 247Enter ASCII Model, 42Enter Ascii Model, 20, 329Enter ASCII Model Selection, 42Enter Ascii Model Selection, 20, 341Errors In Variables, 21, 44, 303Find Resonances, 43Given Exponential, 20, 40, 137Given Polynomial Order, 285Image Model Selection, 415Image Pixel, 21, 45, 411
Image Pixel Model Selection, 22, 45Inversion Recovery, 20, 40, 151Kernel Density Function, 361Linear Phasing, 21, 44, 395Magnetization Transfer, 20, 42, 265Magnetization Transfer Kinetics, 20, 43, 275Maximum Entropy Method Of Moments, 21,
44, 373Metabolic Analysis, 21, 43, 219Non-Linear Image Phasing, 21, 45, 405Polynomials
of Given Order, 21, 44of Unknown Order, 21, 44
Test ASCII Model, 42Test Ascii Model, 20, 337Unknown Number of Exponentials, 20, 40,
143Unknown Polynomial Order, 293
Parameter File, 42Number Of
Abscissa, 458Data Columns, 458Model Vectors, 458Priors, 458
Prior Probability, 459Amplitude, 460High, 459Low, 459Mean, 459NonLinear, 460Ordered, 460Parameter File, 459Peak, 459Prior Type, 460Standard Deviation, 459
Phase Cycling, 162Plot Results Viewer, 71Plots
Data and Model, 81Data, Model and Residuals, 81Expected Log Likelihood, 88Logarithm of the Posterior Probability, 91Maximum Entropy Histogram, 84Maximum Entropy Histograms, 83McMC Samples, 83, 85Parameter Vs Posterior Probability, 86, 87
496 INDEX
Posterior Probability, 82Posterior Probability Vs Parameter Value,
86Residuals, 81Scatter, 88, 91
png graphics, 59Posterior Probability Vs Parameter Value, 86Power Spectrum, 112, 123, 124Prior Probabilities
Bayes Phase, 399Big Magnetization Transfer, 261Big Peak/Little Peak, 212Diffusion Tensor, 253Enter Ascii Model, 331, 333Errors In Variables, 306Magnetization Transfer, 269Magnetization Transfer Kinetics, 279Non-Linear Phasing PackageA, 408θ, 408
Prior Probability, 42, 65, 65Exponential, 67, 459Gaussian, 67, 104, 106, 459Jeffreys’, 118Normalization Constant, 67Parameter, 68, 459Positive, 68, 460Uniform, 67, 103, 118, 459
Prior Viewer, 65, 93Probabilities
Expected Log Likelihood, 453Likelihood, 453Posterior, 453Prior, 453
Product Rule, 99, 119, 344, 439
ReferencingSetting, 59
ReportsAccepted File, 76McMC Values File
General Description, 449Maximum Posterior Probability Simula-
tions, 451Mean Values, 452Prior, 450
Standard Deviations, 453Restoring An Analysis, 22, 35, 40ROI
Expanding, 63Pixels, 63Point, 62Polygon, 62Square, 62
Saving An Analysis, 35, 39Schuster Periodogram, 112, 123Screen Captures, 49Settings
httpd server, 19Software
Bayes Account, 29CC, 29Fortran, 29Installation, 29javaws, 29OS requirements, 29root requirements, 30
Start Up Window, 22, 33Steepest Descents, 173Subdirectories, 469
Bayes, 39Bayes.model.fid, 470Bayes.Predefined.Spec, 469Bayes.test.data, 39BayesAnalyzeFiles, 470BayesAsciiModels, 93, 469BayesOtherAnalysis, 35, 73, 470fid, 36, 53images, 36, 38, 39, 59, 470model.compile, 470plugins, 470Properties, 470Resources, 470Spectroscopic
fid, 470Working Directories, 470
Subroutine Names, 464Sufficient Statistics, 122
Definition, 105Location Parameter, 108
Sum Rule, 100, 119, 344, 440
INDEX 497
Test Ascii Model Package, 337Reports
Bayes Accepted, 339Mcmc Values, 339
Using, 339, 428Viewers
Ascii Data, 337Fortran/C Models, 337Prior Probabilities, 337
WidgetsBuild, 337Find Outliers, 339System, 337User, 337
Thermodynamic Integration, 445, 449
Uninstall, 49Unknown Number of Exponentials Package, 143
Bayesian Calculations, 145Model Equation, 145Reports
Bayes Accepted, 143, 148Condensed, 148Console Log, 148, 149McMC Values, 148Prob Model, 148
Using, 143Viewers
File, 148Plot Results, 149, 150Prior, 143Text, 148
WidgetsConstant, 143Find Outliers, 143Order, 143
Unknown Polynomial Order Package, 293Bayesian Calculations, 295Files
Ascii, 293Bayes Analyze, 293Peak Pick, 293
Model Equation, 295Number of data sets, 293Reports
Bayes Accepted, 293, 299
Condensed, 299Console Log, 298, 299McMC Values, 299Polynomial Order Plot , 301Prob Model, 299
Using, 293Viewers
File, 299Text, 299
WidgetsSet Order, 293, 294Unknown Order, 293, 294
Viewers, 27, 52ASCII Data, 36Ascii Data, 27, 53, 56, 63, 137, 265, 275,
285, 293, 311, 329, 337, 341Expanding Plot, 53Printing, 53Right click, 53
Bayes Model, 160Fid Data, 27, 265fid Data, 53, 53, 285, 293
Auto Range, 59Autoscale, 56Clear Cursors, 56Clear Data, 57Copy, 59Cursor, 56Data Info, 57Expand, 56fn, 57Full, 56Get Peak, 56Phase Popup, 57Print, 59Properties, 59Referencing, 59Save As, 57, 59Set Preference, 57Units, 59Zoom, 59
Fid Model, 27fid Model, 68, 186
Build BA Model, 70, 159Data, 71
498 INDEX
Horizontal, 71Model, 71Overlay, 71Report, 71Residual, 71Stacked, 71Trace, 71Vertical, 71
File, 28, 80Fortran/C Models, 93, 330Image, 27, 59, 415
Autoset Grayscale, 61Copy Selected, 62Delete All, 61Delete Selected, 61Display Full, 61Element Selection, 60Export, 62Get Statistics, 64, 65Get Threshold Statistics, 65Grayscale, 63Image Selection, 60List, 59Load Selected Pixels, 61Max, 64Mean, 64Min, 64Right Click, 61RMS, 64Save Displayed, 62Save Statistics, 65Sdev, 64Set Image Area, 62Show Histogram, 61Show Info, 62Slice, 62Slice Selection, 60Statistics, 60Value, 64View Selected Pixels, 61Viewer Settings, 62Viewing, 62X Pos, 64Y Pos, 64
Plot Results, 28, 71Prior, 27, 65
Prior Probabilities, 138, 312Text, 141, 271, 281, 290, 309, 322, 335, 353Text Results, 26, 28, 52, 74
Bayes Analyze, 176
WidgetsAnalyze Image Pixel Package
Build, 411Find Outliers, 411Get Statistics, 413System, 411User, 411
Analyze Image Pixel Unique PackageBuild, 423Find Outliers, 423Get Statistics, 425System, 423User, 423
Ascii Data ViewerDelete, 53Left-mouse, 53Right-mouse, 53
Bayes Analyze PackageBy, 158, 176First Point, 163From, 158, 176Imag Offset, 163Mark, 159Max New Res, 157New, 159Noise, 158Phase, 157Primary, 158Real Offset, 163Remove, 159Remove All, 159Reset, 159, 193Restore, 159Save, 159Secondary, 159Shim Order, 157, 163Signal, 158To, 158, 176
Bayes Find Resonances PackageBuild FID Model, 240, 241, 246Constant, 239, 242
INDEX 499
First Trace, 239Last Trace, 239Model Fid Number, 241Phase Model, 239, 242
Bayes Metabolite PackageFid Model, 221Fid Model Viewer, 221Load System Metabolite File, 219Load System Resonance File, 221Load User Metabolite File, 219Load User Resonance File, 221Shift Left, 221, 222Shift Right, 221, 222
Bayes Test Data Package# Images, 427# Slices, 427Abscissa, 427ArrayDim, 427Build, 427Get Job, 428Max Value, 427Noise SD, 427Pe, 427Ro, 427Run, 428Set (server), 428Status, 428System, 427User, 427
Big Magnetization Transfer PackageFind Outliers, 259
Big Peak/Little Peak PackageMetabolite, 207Solvent, 207
Diffusion Tensor PackageAbscissa Options, 248Find Outliers, 247Include Constant, 247, 248, 255Tensor Number, 247, 248, 255Use b Matrix, 255Use b Vectors, 254, 255Use g Vectors, 254
Enter Ascii Model PackageFind Outliers, 329System, 329User, 329
Enter Ascii Model Selection PackageFind Outliers, 341System, 341User, 341
Errors In Variables PackageGiven Errors In, 303Order, 303
Fid Data ViewerAutoscale, 56Clear Cursors, 56Cursor A, 56Cursor B, 56Delta, 56Display Type, 56Expand, 56Full, 56Get Peak, 56Left-mouse, 56Options, 57, 59Right-mouse, 56Trace, 70
Fortran/C Model ViewerAbscissa Spinner, 93Add Prior, 96Allow/Disallow Editing, 97Cancel and Exit, 96Changing Models, 94Code, 93, 94Compile Results, 97Compiling, 96Create/Edit Model, 93Data Columns Spinner, 93Derived, 96Edit/Create New Model, 93, 94High, 97Low, 97Mean, 97Model, 96Model Vectors, 93Name (parameter), 97Order, 97Parameter Type, 97Parameters button, 93, 94, 96Prior Type, 97Priors, 96Remove All (priors), 96
500 INDEX
Remove Prior, 96Remove Selected Model, 93Save and Load, 96Standard Deviation, 97
Given Exponential PackageConstant, 137, 139Find Outliers, 137Order, 137, 139
Given Polynomial Order PackageSet Order, 285
GlobalBayes Find Outliers, 27Cancel, 26, 51Edit Servers, 26Get Job, 26, 51, 137, 143, 151, 155, 209,
221, 241, 247, 259, 267, 277, 285, 293,305, 311, 331, 339, 343, 357, 364, 375,413, 417, 425, 428
Reset, 27Restore Analysis, 22Run, 26, 51, 137, 143, 151, 155, 207, 221,
241, 247, 248, 259, 267, 277, 285, 293,305, 311, 329, 337, 343, 357, 364, 373,413, 415, 425, 428
Save, 27Set (server), 26, 52, 137, 143, 151, 155,
207, 221, 239, 247, 259, 265, 277, 285,293, 305, 311, 329, 337, 343, 355, 364,373, 413, 415, 425, 428
Status, 26, 52, 137, 143, 151, 155, 207,221, 241, 247, 259, 267, 277, 285, 293,305, 311, 329, 337, 343, 355, 364, 373,413, 415, 425, 428
Image Model Selection PackageSystem, 415User, 415
Image ViewerElement Number, 62Get Statistics, 64Get Threshold Statistics, 65Grayscale, 63Save Statistics, 65Slice Number, 62Value, 64X Pos, 64Y Pos, 64
Inversion Recovery PackageFind Outliers, 151
Kernel Density Function PackageKernel Type, 364Output Size, 364
Linear Phasing Packagecf, 403Display, 403Display Array Element, 403fn, 403fn1, 403Image Type, 402Load An Image, 402np, 403nv, 403Process, 403
Magnetization Transfer Kinetics PackageLoad, 275, 281Set, 275Uncertainty, 275
Magnetization Transfer PackageFind Outliers, 265
MaxEnt Density Function Estimation Pack-age
Histogram Size, 373Order, 373
Non-Linear Phasing PackageProcess, 409Write Ascii images, 409Write imaginary images, 409
Prior ViewerHigh, 65Low, 65Mean, 65Prior Type, 67
ServerEdit, 52Name, 26, 52, 52Set (server), 48Setup, 48, 52
Test Ascii Model PackageFind Outliers, 339System, 337User, 337
Text Results ViewerCopy, 74
INDEX 501
Down arrow, 74Enable Editing, 74Print, 74Save (a copy), 74Save As, 74Settings, 74Up arrow, 74
Unknown Number of Exponentials PackageConstant, 143Find Outliers, 143Order, 143
Unknown Polynomial Order PackageSet Order, 293, 294Unknown Order, 293, 294
WorkDirCreating, 22, 33, 46Deleting, 22, 33, 46List, 24, 46Loading, 46Name, 46Popup, 47