PAST is a free, easy-to-use data analysis package originally aimed at
paleontology but now also popular in many other fields.
It includes common statistical, plotting and modelling functions:
A spreadsheet-type data entry form
Both interactive user interface and scripting
Graph, scatter, 3D scatter, bubble, histogram, kernel density
estimation, box, percentile, ternary, survivorship, spindle,
matrix, surface and normal probability plots
Curve fitting: Linear (ordinary least squares, Reduced Major Axis, Major Axis, robust)
with bootstrapping and permutation, Durbin-Watson and Breusch-Pagan tests, Generalized
Linear Model including logit regression,
lin-log (exponential), log-log (allometric), polynomial, logistic, von Bertalanffy, Michaelis-Menten,
sum-of-sines, smoothing splines, LOESS smoothing, Gaussian (species packing), multiple
multivariate regression, logarithmic spirals.
F, t, permutation t, Chi-squared w. permutation test, Fisher's exact, Kolmogorov-Smirnov,
Mann-Whitney, Shapiro-Wilk, Jarque-Bera, Anderson-Darling,
Spearman's Rho and Kendall's Tau tests with permutation, correlation and partial
correlation, polyserial correlation, covariance, contingency tables,
one-way and two-way ANOVA, one-way ANCOVA, Kruskal-Wallis test, sign test, Wilcoxon signed
rank test with exact test, Friedman test, Fligner-Killeen test for coefficients of
variation, mixture analysis, survival analysis (Kaplan-Meier curves,
logrank and other tests), risk difference/risk ratio/odds ratio with tests.
Diversity indices with bootstrapping and permutation,
individual- and sample-based rarefaction. Capture-recapture richness estimators.
Renyi diversity profiles, SHE analysis, beta diversity.
Abundance model fitting: Geometric, log-series, log-normal, broken
Multivariate statistics: Principal Components (with Minimal Spanning Tree,
Principal Coordinates (19 distance measures), Non-metric Multidimensional
(19 distance measures), Detrended Correspondence Analysis, Canonical
Correspondence Analysis, Cluster
analysis (UPGMA, single linkage, Ward's method and neighbour joining,
19 distance measures, two-way clustering,
bootstrapping), k-means clustering, seriation,
discriminant analysis, one-way MANOVA, one-way and two-way ANOSIM and NPMANOVA,
Hotelling's T2, paired Hotelling's T2, Mahalanobis-distance permutation,
Mardia's multivariate normality, Box's M, Canonical Variates Analysis,
multivariate allometry with bootstrapping, Mantel test, SIMPER,
Imbrie & Kipp factor analysis, Modern Analog Technique, two-block Partial Least Squares.
Time series analysis: Spectral analysis (including REDFIT and multitaper) autocorrelation, cross-correlation,
wavelet transform, short-time Fourier transform, Walsh transform, runs test, Markov chains. Mantel
correlogram and periodogram. ARMA, Box-Jenkins intervention analysis. Parks-McClellan
filtering, smoothing filters.
Point events analysis. Solar forcing model.
Geometrical analysis: Directional statistics (Rayleigh, Rao, chi-squared,
Watson's U2, Watson-Williams, Mardia-Watson-Wheeler, circular kernel density estimation,
angular mean with CI, rose plots, circular correlation), kernel density estimation of point density,
point distribution statistics (nearest neighbour and Ripley's K), point alignment detection,
coordinate transformations (WGS84, UTM etc.), spatial autocorrelation (Moran's I),
Fourier shape analysis, elliptic Fourier
shape analysis, Hangle shape analysis, eigenshapes, landmark analysis with Bookstein and
Procrustes fitting (2D and 3D),
thin-plate spline transformation grids with expansions and principal strains,
partial warps and scores, relative warps and scores, centroid size from
landmarks, size removal by Burnaby's method.
Parsimony analysis (cladistics): Exhaustive,
branch-and-bound and heuristic algorithms, Wagner, Fitch and Dollo characters.
Bootstrap, strict and majority rule consensus trees. Consistency and retention
indices. Three stratigraphic congruency indices with permutation tests.
Cladograms and phylograms.
Biostratigraphy with the methods of Unitary Associations,
Ranking-Scaling (RASC), Appearence Event Ordination and Constrained
Optimization (CONOP). Confidence intervals on stratigraphic ranges.
Gridding (spatial interpolation): Moving average, thin-plate spline
and kriging with three semivariogram models.
Included in the distribution are real data sets for educational
use, together with extensive documentation and case studies.
PAST has been tested under Windows XP, Vista and Windows 7.
PAST - because your data deserve itTM