        # 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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Last modified Thu Feb 5 12:26:53 CST 2004