Simfit: simulation, statistical analysis, curve fitting and graph plotting.

The Simfit package

Simfit is a completetly free, open-source package, distributed as 32-bit or 64-bit binaries. The source code can be downloaded from https://simfit.org.uk so that programmers can edit the drivers for their own needs or compile individual subroutines.

Summary
Statistics
Curve fitting
Graph plotting
Calculations
Special functions
NAG library routines
Simulations
Documentation
Installation
Help
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Summary

Simfit is a computer package for simulation, statistical analysis, curve fitting and graph plotting, using models from a compiled library or from ASCII text files supplied by the user. It can be used for teaching the principles of curve fitting, simulation and statistical analysis to students, but it will be found most useful by those interested in serious data analysis and creating professional, publication quality, scientific graphs.

Simfit is a collection of forty separate programs, each dedicated to a particular area of data analysis, but the package is run seamlessly from a program manager (w_simfit.exe in 32-bit versions or x64_simfit.exe in 64-bit versions) that has facilities for browsing and printing files. Data can be formatted by dedicated editors that can check for positive values, values in increasing order, sensible weighting factors, etc. or you can copy tables to the clipboard from any Windows application, then paste them into any Simfit program. Macros are provided to create correctly formatted data files from data held in Microsoft Office Excel format.

In order to introduce first-time users to Simfit functionality, each time a procedure is selected a default data set is installed to demonstrate the data format required and the sort of results anticipated. Further, at any stage while using Simfit, the file-open dialogue has a button labeled [Demo] which lists typical data files for browsing or analysis. There is also a button labeled [Keyboard] for users who want to type in small data samples from the console and a button labeled [Paste] to input rectangular data matrices from the clipboard.

Many advisory messages are displayed to help when using a procedure for the first time, but there is a speedup option to toggle these on or off as required.

After each analysis the results are written to archives for retrospective use.

There is a comprehensive reference manual (w_manual.pdf) compete with hyperlinks and an index as well as individual tutorials explaining each Simfit procedure. These are also distributed as a collected set (w_examples.pdf) with the Simfit package.

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Statistics

All the usual descriptive statistics (bar charts, histograms, best-fit distributions on sample cdfs, dendrograms, box and whisker or cluster plots), multivariate statistics (distance matrices and dendrograms, principal components and scree plots), time series (ACF, PACF, ARIMA) and frequently used tests (mostly with exact p values not the normal approximations), such as:

chi-square (O/E vectors, m by n contingency tables and wssq/ndof)
McNemar test on n by n frequency tables
Cochran Q test
Fisher exact (2 by 2 contingency table) with all p values
Fisher exact Poisson distribution test
t (both equal and unequal variances, paired and unpaired)
variance ratio
F for model validation
Bartlett and Levene tests for homogeneity of variance
1,2,3-way Anova (with automatic variance stabilizing transformations and nonparametric equivalents)
Tukey post-ANOVA Q test
Factorial ANOVA with marginal plots
Repeated measures ANOVA with Helmert matrix of orthonormal contrasts, Mauchly sphericity test and Greenhouse-Geisser/Huyn-Feldt epsilon corrections
MANOVA with Wilks lambda, Roy's largest root, Lawley-Hotelling trace, and Pillai trace for equality of mean vectors, Box's test for equality of covariance matrices, and profile analysis for repeated measurements.
Canonical variates and correlations for group comparisons
Mahalanobis distance estimation for allocation to groups using estimative or predictive Bayesian methods
Cochran-Mantel-Haenszel 2x2xk contingency table Meta Analysis test
Binomial test
Sign test
various Hotelling T-squared tests
Goodness of fit and non parametric tests:
- runs (all, conditional, up and down)
- signs
- Wilcoxon-Mann-Whitney U
- Wilcoxon paired-samples signed-ranks
- Kolmogorov-Smirnov 1 and 2 sample
- Kruskal-Wallis
- Friedman
- Median, Mood and David tests and Kendall coefficient of concordance
- Mallows Cp, Akaike AIC, Schwarz SC, Durbin-Watson
- tables and plots of residuals, weighted residuals, deviance residuals, Anscombe residuals, leverages and studentized residuals as appropriate
- half normal and normal residuals plots
Multilinear regression by
- L₁ norm
- L₂ norm (weighted least squares)
- L_∞ norm
- Robust regression (M-estimates)
- Also logistic, binary logistic, log-linear, orthogonal, reduced major axis, with interactive selection and transformation of variables in all cases.
Partial Least squares (PLS)
Survival analysis (Kaplan-Meier, ML-Weibull, Mantel-Haenszel) or, using generalized linear models with covariates (Exponential, Weibull, Extreme value, Cox)
Correlation analysis (Pearson product moment, Kendal Tau, Spearman Rank) on all possible pairs of columns in a matrix, and canonical correlations when data columns fall naturally into two groups. Partial correlation coefficients can be calculated for data sets with more than two variables.
Shapiro-Wilks normality test with the large sample correction
Normal scores plots
Binomial distribution, analysis of proportions, exact parameter confidence limits, likelihood ratio, odds, odds ratios and graphical tests such as log-odds-ratios plots with exact confidence limits for systematic variation in binomial p values
Trinomial distribution (and confidence contour plots)
Parameter estimates, confidence limits and goodness of fit for:
- uniform
- normal
- binomial
- Poisson
- exponential
- gamma
- beta
- lognormal
- Weibull distributions
All possible pairwise comparisons between columns of data by KS-2, MWU and unpaired t tests using the Bonferroni principle.
Calculates False Discovery Rates FDR(HM) given p-values from multiple testing.

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Curve fitting

Sums of exponentials (and estimation of AUC)
Sums of Michaelis-Menten functions (and estimation of half saturation points and final asymptotes)
Sums of High/Low affinity binding sites
Cooperative order n saturation functions (and cooperativity analysis)
Positive n:n rational functions
Growth curves (derivative plots, comparison of models and estimation of min/max growth rates, half-times and final sizes)
Survival curves using several models
Polynomials (all degrees up to 6 then statistical tests for the best model and prediction of x with confidence limits given y)
Cubic splines (user-placed knots, automatic knots with variable tension, or crosss-validation data smoothing)
Systems of differential equations (Adams, Gear, phase portrait, orbits) using defined starting estimates and limits or random cycles to search for a global minimum
Calibration curves (polynomials, splines or user selected models)
Area under curve (AUC by choice from several methods)
Initial rates
Lag times
Horizontal and inclined asymptotes
Numerical deconvolution of sums of exponentials, Michaelis-Mentens, trigonometric functions and Gaussian densities
Fitting user supplied models
Analyzing flow cytometry profiles
After fitting functions of 1, 2 or 3 variables, parameters and objective functions can be stored for F, Akaike, Schwarz and Mallows Cp tests, and the wssq/ndof contours and 3D surface can be viewed as functions of any two chosen parameters. With all functions of 1 variable, calibration, evaluation, extrapolation, area calculations, derivative estimations and interactive error bar plots can be done.
Multi-function mode: simultaneous fitting of several functions of the same independent variables, linked by common model parameters
Generalized Linear Models (GLM) can be fitted interactively with either normal, binomial, Poisson or Gamma errors. Appropriate links can be either identity, power, square root, reciprocal, log, logistic, probit or complementary log-log with canonical links as defaults and facility to supply fixed offsets. A simplified interface is included for logistic, binary logistic or polynomial logistic regression, bioassy, log-lin contingency analysis or survival analysis.
Stratified data sets can be analyzed by Cox regression and conditional logistic regression
Autoregressive integrated moving average models (ARIMA) to time series with forecasting
Facility to store parameter estimates and covariance matrices in order to compute Mahalanobis distances between fits of the same model to different data sets and test for significant differences in parameter estimates.

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Graph plotting

Grouping of data into histograms (with error bars if appropriate) and cdfs
Calculation of means and error bars with arbitrary confidence limits from replicates can be done interactively or from data files
Error bars can be non-symmetrical or sloping if required and multiple non-orthogonal error bars can be plotted
Error bars can be added to 2D and 3D bar charts and 3D cylinder plots
Extrapolation of best-fit linear and nonlinear curves to arbitrary end points
Automatic transformation of error bars into various axes (Hill, Lineweaver-Burk, Scatchard, log-odds, etc.)
Immunoassay type dilution plots using logs to base 2, 3, 4, 5, 6, 7, 8, 9 as well as e and 10, and with labels as logs, powers of the base or fractions
Multiple axes plots
Pie charts with arbitrary displacements, fill-styles, colours
Bar charts with arbitrary positions, sizes, fill-styles, colours and error-bars
Presentation box and whisker plots, and pie or bar charts with 3D perspective effects
Orbits and vector field diagrams for systems of differential equations
Dendrograms and 3D-cluster plots for use in cluster analysis
Scree diagrams and score or loading scatter plots for principal components analysis (score plots can have Hotelling T^2 elliptical confidence regions)
3D-surfaces and 2D-projections of contours
Curves in space and projections onto planes
vast array of plotting characters and maths symbols
Standard PostScript fonts, Symbol, ZapfDingbats and Isolatin1 encoding
Professional quality PostScript files that can easily be edited to change titles, legends, symbols, line-types and thicknesses, etc.
Interactive PostScript facility for arbitrarily stretching and clipping overcrowded plots such as dendrograms without changing aspect ratios of fonts or plotting symbols but by just changing white-space between graphical objects
A PostScript editor is supplied for scaling, rotating, shearing, translating, editing, making collages and inlays from .eps files
Transformation of .eps files into bit-map and compressed graphics formats (e.g. bmp, pcx, tif, jpg, png, pdf)
Plotting user defined parameteric equations such as r(theta), x(t), y(t) in 2-space and x(t),y(t),z(t) in 3-space
Facility to import PostScript specials automatically into the PostScript file creation stream in order to redefine fonts, colours, plotting symbols, add logos, etc.
Graphical deconvolution of summation models after fitting
2D and 3D Biplots for multivariate data sets

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Calculations

Zeros of polynomials
Zeros of a user-defined function
Zeros of n nonlinear functions in n variables
Integrals of n user-defined functions in m variables
Convolution integrals
Bound-constrained quasi-Newton optimization
Eigenvalues
Determinants
Inverses
Singular value decomposition with right and left singular vectors
LU factorisation as A = PLU with matrix 1 and infinity norms and corresponding condition numbers
QR factorisation as in A = QR
Cholesky factorisation as in Q = R(R^T)
Matrix multiplication C = AB, (A^T)B, A(B^T) or (A^T)(B^T)
Evaluation of quadratic forms (x^T)Ax or (x^T)(A^{-1})x
Solve full-rank matrix equations Ax = b
Solve over-determined linear systems Ax = b in the L₁, L₂ or L_∞ norms
Solve the symmetric eigenvalue problem (A - lambda*B)x = 0
Areas, derivatives and arc lengths of user supplied functions
Analysis of cooperative ligand binding (zeros of binding polynomial, Hessian, minmax Hill slope, transformed binding constants, cooperativity indices, plotting species fractions)
Power and sample size calculations for statistical tests used in clinical trials, including plotting power as a function of sample size (1 or 2 binomial proportions; 1, 2 or k normal ANOVA samples; 1 or 2 correlation coefficients; 1 or 2 variances; chi-square test)
Probabilities and cdf plots for the non-central t, non-central chi-square, non-central beta or non-central F distributions
Estimation of exact parameter confidence limits for the binomial, normal, Poisson, etc. distributions and plotting confidence contours for the trinomial distribution.
Robust calculation of location parameter with confidence limits for one sample (median, trimmed and winsorized means, Hodges-Lehmann estimate, etc.).
Time series smoothing by moving averages, running medians, Hanning or the 4253H-twice smoother
Time series, sample autocorrelation functions and partial autocorrelation functions and plots for chosen numbers of lags and associated test statistics
Auto- and cross-correlation matrices for two time series
Distance matrices for use in cluster analysis with extensive choice of pre-conditioning transformations and alternative link functions, e.g. Canberra dissimilarity and Bray-Curtis similarity.
Neaest neighbours from a distance matrix
Classical-metric and non-metric scaling of distance matrices
Principal components with eigenvalues, scree diagrams, loadings and scores from multivariate data sets
Procrustes analysis to estimate the similarity between two matrices
Varimax or Quartimax rotation of a loading matrix
Canonical variates with eigenvalues, scree diagrams, loadings and scores from multivariate data sets. Group means can be plotted with confidence regions to assign comparison data to existing groups.
K-means cluster analysis with plots
Shannon, Brilloin, Pielou, and Simpson diversity indices.
Kernel density estimation
Smooth interpolation by cubic Bessel, piecewise monotonic, McConalogue, Butland

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Special functions

These can all be called by 1-line commands as described in the documentation for user-defined models. Some of them have equivalent NAG library versions as indicated below.

 Command       NAG    Description
 arctanh(x)    S11AAF Inverse hyperbolic tangent
 arcsinh(x)    S11AAF Inverse hyperbolic sine
 arccosh(x)    S11AAF Inverse hyperbolic cosine
 ai(x)         S17AGF Airy function Ai(x)
 dai(x)        S17AJF Derivative of Ai(x)
 bi(x)         S17AHF Airy function Bi(x)
 dbi(x)        S17AKF Derivative of Bi(x)
 besj0(x)      S17AEF Bessel function J0
 besj1(x)      S17AFF Bessel function J1
 besy0(x)      S17ACF Bessel function Y0
 besy1(x)      S17ADF Bessel function Y1
 besi0(x)      S18ADF Bessel function I0
 besi1(x)      S18AFF Bessel function I1
 besk0(x)      S18ACF Bessel function K0
 besk1(x)      S18ADF Bessel function K1
 phi(x)        S15ABF Normal cdf
 phic(x)       S15ACF Normal cdf complement
 erf(x)        S15AEF Error function
 erfc(x)       S15ADF Error function complement
 dawson(x)     S15AFF Dawson integral
 ci(x)         S13ACF Cosine integral Ci(x)
 si(x)         S13ADF Sine integral Si(x)
 e1(x)         S13AAF Exponential integral E1(x)
 ei(x)         ...... Exponential integral Ei(x)
 rc(x,y)       S21BAF Elliptic integral RC
 rf(x,y,z)     S21BBF Elliptic integral RF
 rd(x,y,z)     S21BCF Elliptic integral RD
 rj(x,y,z,r)   S21BDF Elliptic integral RJ
 sn(x,m)       S21CAF Jacobi elliptic function SN
 cn(x,m)       S21CAF Jacobi elliptic function CN
 dn(x,m)       S21CAF Jacobi elliptic function DN
 ln(1+x)       S01BAF ln(1 + x) for x near zero
 mchoosen(m,n) ...... Binomial coefficient
 gamma(x)      S13AAF Gamma function
 lngamma(x)    S14ABF log Gamma function
 psi(x)        S14ADF Digamma function, (d/dx)log(Gamma(x))
 dpsi(x)       S14ADF Trigamma function, (d^2/dx^2)log(Gamma(x))
 igamma(x,a)   S14BAF Incomplete Gamma function
 igammac(x,a)  S14BAF Complement of Incomplete Gamma function
 fresnelc(x)   S20ADF Fresnel C function
 fresnels(x)   S20ACF Fresnel S function
 bei(x)        S19ABF Kelvin bei function
 ber(x)        S19AAF Kelvin ber function
 kei(x)        S19ADF Kelvin kei function
 ker(x)        S19ACF Kelvin ker function
 cdft(x,m)     G01EBF cdf for t distribution
 cdfc(x,m)     G01ECF cdf for chi-square distribution
 cdff(x,m,n)   G01EDF cdf for F distribution (m = num, n = denom)
 cdfb(x,a,b)   G01EEF cdf for beta distribution
 cdfg(x,a,b)   G01EFF cdf for gamma distribution
 invn(x)       G01FAF inverse normal
 invt(x,m)     G01FBF inverse t
 invc(x,m)     G01FCF inverse chi-square
 invb(x,a,b)   G01FEF inverse beta
 invg(x,a,b)   G01FFF inverse gamma
 spence(x)     ...... Spence integral: 0 to x of -(1/y)log|(1-y)|
 clausen(x)    ...... Clausen integral: 0 to x of -log(2*sin(t/2))
 struveh(x,m)  ...... Struve H function order m (m = 0, 1)
 struvel(x,m)  ...... Struve L function order m (m = 0, 1)
 kummerm(x,a,b)...... Confluent hypergeometric function M(a,b,x)
 kummeru(x,a,b)...... U(a,b,x), b = 1 + n, the logarithmic solution
 lpol(x,m,n)   ...... Legendre polynomial of the 1st kind, P_n^m(x),
                      -1 =< x =< 1, 0 =< m =< n
 abram(x,m)    ...... Abramovitz function order m (m = 0, 1, 2), x > 0,
                      integral: 0 to infinity of t^m exp( - t^2 - x/t)
 debye(x,m)    ...... Debye function of order m (m = 1, 2, 3, 4)
                      (m/x^m)[integral: 0 to x of t^m/(exp(t) - 1)]
 fermi(x,a)    ...... Fermi-Dirac integral (1/Gamma(1 + a))[integral:
                      0 to infinity t^a/(1 + exp(t - x))]
 heaviside(x,a)...... Heaviside unit function h(x - a)
 delta(i,j)    ...... Kronecker delta function
 impulse(x,a,b)...... Unit impulse function (small b for Dirac delta)
 spike(x,a,b)  ...... Unit triangular spike function
 gauss(x,a,b)  ...... Gauss pdf
 sqwave(x,a)   ...... Square wave amplitude 1, period 2a
 rtwave(x,a)   ...... Rectified triangular wave amplitude 1, period 2a
 mdwave(x,a)   ...... Morse dot wave amplitude 1, period 2a
 stwave(x,a)   ...... Sawtooth wave amplitude 1, period a
 rswave(x,a)   ...... Rectified sine wave amplitude 1, period pi/a
 shwave(x,a)   ...... Sine half-wave amplitude 1, period 2*pi/a
 uiwave(x,a,b) ...... Unit impulse wave area 1, period a, width b

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NAG library routines

Early versions of Simfit used the NAG library routines for numerical procedures, and this can still be done if a valid license is available. Otherwise Simfit has a built-in library to use public domain versions of these routines. Some of these replacement routines have additional functionality and, where routines have been removed from the NAG library, additional code has been included so that newer NAG routines will be called when the NAG library is being used instead of the Simfit library.

a00acf, a00adf
c02agf
c05adf, c05azf, c05nbf
d01ajf, d01eaf
d02cjf, d02ejf
e02adf, e02akf, e02baf, e02bbf, e02bcf, e02bdf, e02bef, e02gbf, e02gcf
e04jyf, e04kzf, e04uef, e04uff
f01abf, f01acf, f01adf
f02aaf, f02aff, f02ebf, f02fdf
f03aaf, f03abf, f03aef, f03aff
f04aff, f04agf, f04ajf, f04asf, f04atf
f06eaf, f06ejf, f06qff, f06yaf, f06raf
f07adf, f07aef, f07agf, f07ajf, f07fdf
f08aef, f08aff, f08faf, f08kaf, f08kef, f08kff, f08mef, f08naf, f08saf
fz1caf, fz1clf
g01aff, g01bjf, g01bkf, g01cef, g01dbf, g01ddf, g01eaf, g01ebf, g01ecf, g01edf, g01eef, g01eff, g01emf, g01faf, g01fbf, g01fcf, g01fdf, g01fef, g01fff, g01fmf, g01gbf, g01gcf, g01gdf, g01gef
g02baf, g02bnf, g02byf, g02caf, g02gaf, g02gbf, g02gcf, g02gdf, g02gkf, g02haf, g02laf, g02lcf, g02ldf
g03aaf, g03acf, g03adf, g03baf, g03bcf, g03caf, g03ccf, g03daf, g03dbf, g03dcf, g03eaf, g03ecf, g03eff, g03ejf, g03faf, g03fcf
g04adf, g04aef, g04agf, g04caf
g05caf, g05cbf, g05ccf, g05daf, g05dbf, g05dcf, g05ddf, g05def, g05dff, g05dhf, g05dpf, g05dyf, g05ecf, g05edf, g05ehf, g05eyf, g05fff, g05kff, g05kgf, g05ncf, g05saf, g05scf, g05sdf, g05sff, g05sjf, g05skf, g05slf, g05smf, g05snf, g05sqf, g05ssf, g05taf, g05tdf, g05tjf, g05tlf
g07aaf, g07abf, g07bef, g07daf, g07ddf, g07eaf, g07ebf
g08aaf, g08aef, g08acf, g08baf, g08daf, g08eaf, g08aff, g08agf, g08ahf, g08ajf, g08akf, g08baf, g08cbf, g08cdf, g08daf, g08eaf, g08raf, g08rbf
g10abf, g10acf, g10baf, g10zaf
g11caf
g12aaf, g12baf, g12zaf
g13aaf, g13abf, g13acf, g13adf, g13aef, g13ahf
s01baf
s11aaf, s11abf, s11acf
s13aaf, s13acf, s13adf
s14aaf, s14abf, s14acf, s14adf, s14baf
s15abf, s15acf, s15adf, s15aef, s15aff
s17acf, s17adf, s17aef, s17aff, s17agf, s17ahf, s17ajf, s17akf
s18acf, s18adf, s18aef, s18aff
s19aaf, s19abf, s19acf, s19adf
s20acf, s20adf
s21baf, s21bbf, s21bcf, s21bdf, s21caf
x01aaf, x02ajf, x02alf, x02amf, x03aaf

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Simulation

Generating exact data from a library of models or from user-defined models
User defined models can be multiple equations in several variables or sets of nonlinear differential equations, and can have conditional logical branching (equivalent to if...elseif...else) for models that swap at critical values of subsidiary functions or independent variables
Logical operators like IF, IFNOT, AND, OR, NOT, XOR, etc. can be used to control model execution
Special functions that can be used within models include
- Airy functions Ai(x), Bi(x) and derivatives
- Hyperbolic and inverse hyperbolic functions cosh(x), sinh(x), tanh(x), arccosh(x), arcsinh(x), arctanh(x)
- Bessel functions J0, J1, Y0, Y1, I0, I1, K0, K1
- Normal integral phi(x), error function erf(x) and complements phic(x) and erfc(x), Dawson's integral
- Exponential, sine and cosine integrals, E1(x), Ei(x), Si(x), Ci(x)
- Fresnel, Spence, Debye, Fermi-Dirac, Abramovitz, Clausen integrals
- Kelvin bei(x), ber(x), kei(x) and ker(x) functions
- Elliptic integrals RC, RF, RD, RJ and Jacobi functions sn(u,m), cn(u,m) and dn(u,m)
- Binomial coefficients, gamma function, incomplete gamma function, log(gamma(x)), digamma (psi(x)), and trigamma functions
- Struve confluent hypergeometric functions
- Legendre polynomials of degree n and order m, spherical harmonics
- Cumulative distribution functions for the normal, t, F, chi-square, beta and gamma distributions
- Inverse functions for the normal, t, F, chi-square, beta and gamma distributions
- Impulse functions: Heaviside, Kronecker delta, Dirac delta, triangular spike, Gaussian
- Periodic wave impulse functions: square, rectified triangle, Morse dot, sawtooth, rectified sine, rectified half sine, unit impulse
One-line commands can be used for vector arithmetic (initialisation, norms, dot products), for evaluating polynomials or Chebyshev expansions, or for calling for mathematical constants (like Euler's gamma)
Submodels can be defined, and these can be called from a main model for function evaluation, root finding, or adaptive quadrature or they can be called dynamically with arbitrary arguments
A one line command is all that is necessary to estimate a convolution integral for any two sub-models over any range
Adding random error to exact data sets to simulate experimental error
Systems of differential equations
After simulating, selected orbits can be stored and, with autonomous systems, vector field phase portraits can be plotted to identify singularities.
Generating random numbers and 1,2,3-D random walks from the:
- uniform
- normal
- chi-square
- F
- logistic
- Weibull
- Cauchy
- Poisson
- binomial distributions.
Generating n by m normally distributed random matrices.
Generating random permutations of lists and Latin squares.

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Documentation

Help documents are available in several formats as follows:
- ASCII text files can be read by any text editor (e.g. Notepad), or using a Simfit viewer, which is safer as it does not allow editing.
- HTML documents can be viewed by a built in HTML interpreter without using your own browser.
- PostScript documents (.ps) can be read using GSview or transformed into Portable Document Format.
- Portable Document Format (.pdf) files can be read and printed using Adobe Acrobat reader.
- Binary files that can only be read using a built in interpreter.
A short HTML program can be viewed from the main Simfit program manager, w_simfit.exe.
Each program has a dedicated self contained tutorial.
Many of the specialized controls have individual tutorials.
There is an extensive set of readme files (w_readme.0 gives details) which describe advanced features and technical details.
A document (simfit_summary.pdf) summarizes the package and contains collages.
A document (MS_office.pdf) describes the interface to MS Office and, in particular, explains how to use the macros to extract data from MS Excel spreadsheets.
A document (PS_fonts.pdf) lists the PostScript font encodings, for those who want to create special effects.
A detailed reference manual (w_manual.pdf) is provided in monochrome, colour, .ps and .pdf formats. The coloured pdf version incorporates hyperlinks between the contents, index and page references and provides book marks.
A document (source.pdf) explains how to compile the source code.
A document (speedup.pdf) explains how to speed up Simfit analysis by suppressing advisory messages intended for first-time users.
There is a full set of test files containing appropriate data to test every Simfit procedure.

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Installation

Copy down the file simfit_setup7_a_b.exe (or x64_simfit_setup7_a_b.exe) onto your PC, open it and accept the default installation folder.
Make a desk top shortcut to the driver file w_simfit.exe (or x64_simfit.exe) in the ...\Simfit\bin folder.
To run Simfit double click on the desktop icon.
Use the [Configure], [Check], [Apply] options to configure the package.
Other software:
You need a PDF viewer such as sumatraPDF or Adobe Acrobat Reader, and GSview could be useful to view *.EPS files and transorm *.EPS into *.SVG.

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Help

Requests for help may be answered by:

W.G.Bardsley
University of Manchester
Email: bill.bardsley@simfit.org.uk

I always repair errors and will usually help simfit users, including adding new mathematical models to the library.