Summary of MacAnova 4.13 Features

• Variables and operations
  • Named real, logical and character vectors, matrices and arrays, plus structures and graph variables
  • Coordinate labels for vectors, matrices and arrays
  • Usual arithmetic (+, -, *, /, ^ or **) plus modular division (%%) and bit manipulation (%&, %|, %^, %!)
  • Most operators and many functions work with structures, allowing analysis of non-rectangular data sets.
  • Descriptive notes can be attached to all variables
• Help
  • On-line usage summaries and complete help for over 550 topics in 8 automatically searched files
  • HTML help you can read in your favorite web browser
• Descriptive statistics
  • Means, variances, medians, quartiles, extremes, skewness, kurtosis
  • Cross tabs and cell means, variances, standard deviations and extremes, plus cell covariance matrices for multivariate data.
• Linear and generalized linear models
  • A linear model grammar with multiple error terms and shortcuts for polynomial and periodic regressions
  • Up to 96 variables, up to 31 of which can be categorical factors
  • "On the fly" transformations of response and predictor variables
  • ANOVA, MANOVA and regression with optional weights
  • Robust ANOVA and regression
  • Logistic, probit and Poisson regression
  • Iterative proportional fitting
  • Model coefficients, standard errors, contrasts
  • Residual plots and macros to summarize residuals
  • Branch and bound determination of best subset regression with ability to force in a subset and save the models selected
  • Macros for step-wise regression
  • Power and sample size functions for CRD and RBD
  • t-tests, confidence intervals
  • Expected mean squares
  • Macro for non-linear least squares
• Matrix algebra
  • Matrix multiplication (operators %*%, %c% and %C%) and inversion
  • Linear equation solution (operators %/% and %\%)
  • Eigenvalues and eigenvectors and relative eigenvalues and eigenvectors
  • Cholesky, QR and SVD decompositions
  • Beaton sweep operator
  • Trace, diagonal, determinant, outer products, and other matrix and vector manipulations
  • Permutation of dimensions of matrices and arrays
  • Other operations such as Kronecker products and Moore-Penrose inverses are provided as macros
• Time series
  • Fast Fourier transforms (maximum prime factor of length is 29)
  • Convolution and sums of lagged products
  • Forward and backward autoregression and moving average operators
  • Yule-Walker solver and its inverse
  • ACF to partial ACF and its inverse
  • Spectrum and cross-spectrum analysis, including multi-taper
  estimation
  • Macros for least squares and maximum likelihood estimation of ARIMA models, including seasonal models
  • Macros for Hannan-Rissanen and innovations estimation of ARIMA models
  • Macros for computing approximate covariances and variances of autocorrelations using Bartlett's formula
  • Macros to compute the autocovariance function and the spectrum corresponding to an ARMA model
  • Time series plots
  • Frequency function plots
• Multivariate analysis
  • MANOVA
  • Hierarchical cluster analysis
  • K-means cluster analysis
  • Macros related to discrimination and factor analysis, including stepwise discriminant analysis
  • Macros for ULS, GLS and ML factor extraction
  • Varimax, quartimax, equimax and orthomax factor rotation
• Design of experiments
  • Confounding 2 and 3 series factorials
  • Finding aliases in 2 and 3 series fractional factorials
  • Choosing generators and design points in 2 series fractional factorials
  • Canonical analysis of 2nd order response surface
  • Constrained maximization of quadratic functions
  • Recovery of interblock information in incomplete block designs
  • REML analysis of unbalanced models with fixed and random terms
  • "ANOVA" estimates of random effect variances in mixed effects
  • Expectation of mean squares in mixed models analysis of variance
• Random numbers and probabilities
  • Uniform, normal, Poisson and binomial pseudo-random number generators
  • Cumulative and inverse normal, chisquare, F, t, beta, gamma
  • Cumulative and inverse noncentral chisquare
  • Cumulative non-central F, beta and t
  • Cumulative poisson and binomial
  • Cumulative and inverse Studentized range
  • Cumulative and inverse Dunnett's t
• Graphical features
  • Scatter plots, including several y's vs one x
  • Line and impulse plots
  • Box plots, histograms and stem and leaf displays
  • Interaction plots
  • Panel graphs, rectangular arrays of small graphs, including scatterplot matrix
  • Contour plots with interactively labelled contours
  • Stepwise construction of graphs
  • Replotting with changed labels, bounds and tick marks
  • Mouse specification of locations for points and lines on a graph
  • GRAPH variables encapsulating all the information in a graph
  • Graphs are saved when you save your workspace and redrawn when you restore the workspace
• Transformations
  • max, min, sum, prod, all operating on columns of matrices
  • Usual transcendentals
  • Rational functions (ratios of polynomials)
  • Ordering, ranking, sorting
• Importing and exporting data
  • Direct importing of data from spreadsheets using the clipboard
  • Direct exporting of data and results to other programs using the clipboard
  • Reading and writing named data sets from and to plain text files
  • Reading unstructured data together with variable names from plain text files
• Programmability
  • Macros used just like functions
  • Many built-in macros plus 8 files of loadable macros (general, time series, ARIMA modeling, design of experiments, regression, multivariate analysis, graphics, and mathematics)
  • Functions for automatic checking of macro arguments
  • Automatic searching for macros that have not yet been loaded
  • For and while loops, if, else, elseif, break, next, return
• User functions
  • Dynamic loading and execution of user compiled code with callbacks to MacAnova functions.

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