Package index • tdaR

Running TDA and reading its output

The command-file interface, TDA’s help, the methods of fitted objects, convergence control, and accounting for what a run printed.

tdaR tdaR-package: tdaR: Transition Data Analysis
print(<tda_mds>) print(<tda_freq2>) print(<tda_ragged>) print(<tda_graph>) print(<tda_iv>) print(<tda_ivstat>) print(<tda_ps>) plot(<tda_ps>) print(<summary.tda_fit>) print(<tda_ple>) summary(<tda_ltb>) print(<summary.tda_ltb>) print(<tda_fit>) print(<tda_ltb>) print(<tda_table>) plot(<tda_table>) print(<tda_expr>) plot(<tda_sdvd>) plot(<tda_sd_ps3>) print(<tda_spatial>) print(<tda_result>) summary(<tda_result>) logLik(<tda_result>) coef(<tda_result>): Methods for fitted TDA models
tda_run() tda_run_cf(): Run TDA commands
tda_help() tda_time() tda_memory(): TDA's manual, and two notes about the session
tda_manual_map manual_map: Where the manual's remaining commands live in R
tda_options: TDA options not exposed as named arguments
tda_read_table() tda_read_blocks() tda_blocks() tda_file(): Read TDA's output files
tda_payload(): Extract a command's result section from TDA output
tda_output_audit(): Account for every line of a run's printed output
tda_diagnostics(): Diagnostics TDA printed during a run
tda_output() tda_estimates(): Estimates and raw output
tda_control() tda_strict() tda_converged(): Convergence control

Data

The example data, building TDA’s input, variables and random numbers.

tda_rrdat(): The job-episode data from Blossfeld and Rohwer
tda_interval_wages(): Artificial interval-valued wage data
tda_write_data() tda_nvar() tda_block(): Build TDA's input
tda_pdatr(): Print all case pairs
tda_ndvar(): Dummy variables
tda_derive(): Derive variables with TDA's expression language
tda_recode(): Recode variables in place
tda_repsel(): Repeat or select block cases
tda_strings(): String variables from a run
tda_cwt_norm(): Rescale case weights the way TDA's cwt(wnorm=) does
tda_dblock(): Declare a block structure
tda_rd() tda_rdn(): Random values, as TDA's rd()/rdn()
tda_rng() tda_runif() tda_rnorm(): TDA's random number generator

Reading and writing files

Statistical packages, spreadsheets, archives, spatial and other formats, and TDA’s record-file utilities.

tda_read_spss(): Read an SPSS data file
tda_read_stata(): Read a Stata file
tda_read_sys(): Read a TDA system file
tda_read_xls(): Read an Excel .xls workbook
tda_read_dbf(): Read a dBase (.dbf) attribute table
tda_read_ucinet(): Read a UCINET file
tda_read_shapefile(): Read a shapefile into a TDA spatial structure
tda_read_e00() tda_read_gshhs() tda_read_dcw(): Read other spatial formats
tda_gtopo(): Read a GTOPO30 elevation profile
tda_rcsv(): Read a CSV file through TDA
tda_rsys(): Read a TDA system file
tda_rplz(): Read a PLZ-style CSV file
tda_esort() tda_eskip() tda_eselect() tda_emerge() tda_ejoin(): TDA's file utilities
tda_ccnt() tda_lcnt() tda_dump() tda_dsplit(): Inspect a raw file
tda_write_spss() tda_write_stata() tda_write_sys(): Write a data frame to SPSS, Stata or a TDA system file
tda_arcd(): Open or close a TDA data archive
tda_arcv(): Print archive variables
tda_arcvc(): Check a variable description file
unzoo() zoo(): Read and write Zoo archives

Descriptive statistics

Summaries, frequency tables, correlation and covariance, inequality and segregation measures, replication weights.

tda_dstat() tda_corr(): Descriptive statistics
tda_freq() tda_freq1() tda_freq2(): One- and two-way frequency tables
tda_quant() tda_atab(): Quantiles, histograms and one-way frequency tables
tda_rcorr(): Rank correlation matrix
tda_cov(): Covariance matrix
tda_brr(): Balanced repeated replication design
tda_ineq(): Inequality measures
tda_segr(): Segregation measures between two groups
tda_subm(): Substitution-metric distance between distributions
tda_independence(): Delta-independence of two integer variables

Episode data and transition rate models

Episode splitting, life tables, product-limit and interval-censored estimation, rate models, user-defined rate models.

tda_episodes() tda_state_dist(): The episode data behind a model
tda_split(): Split episodes at a time-varying covariate
tda_transitions(): Transitions covered by a fit
tda_dple() tda_dltb() tda_diple() tda_ltb() tda_ple() tda_km(): Life tables, Kaplan-Meier, and the discrete time estimators
tda_mple(): Product-limit (Kaplan-Meier) distribution and jumps
tda_midf(): Distribution function bounds and estimate for interval-censored data
tda_midf1(): Uniform-model CDF for interval-censored data, at each observation
tda_midf2(): Restricted mean for interval-censored data, at each observation
tda_midf3(): Average nearby endpoints for interval-censored data
tda_survivor(): The survivor function as a single table
tda_rates(): The estimated rate as a single table
vcov(<tda_fit>) confint(<tda_fit>) logLik(<tda_fit>) summary(<tda_fit>) anova(<tda_fit>) predict(<tda_fit>) fitted(<tda_fit>) residuals(<tda_fit>) TDA_MODELS tda_rate() tda_coxph() tda_estimates.tda_fit() coef(<tda_fit>) nobs(<tda_fit>): Transition rate models
tda_rap(): Rates in age-period form
tda_constrain(): Build a linear parameter constraint
tda_frml(): Maximum likelihood for a user-defined transition rate model
tda_gdf(): General distribution functions for censored data
plot(<tda_ple>) plot(<tda_ltb>) plot(<tda_rate>): Plot survivor curves and fitted rates

Regression

tda_lsreg() tda_lsreg1(): Least squares regression
TDA_FAMILIES tda_glm(): Generalized linear models
TDA_QRMODELS tda_qreg(): Qualitative response models
tda_loglin() coef(<tda_loglin>) vcov(<tda_loglin>) residuals(<tda_loglin>) print(<tda_loglin>): Log-linear models of a contingency table
tda_l1reg(): Least absolute deviations regression
tda_freg(): Non-linear regression with a user-defined function
tda_mreg(): Monotone regression
tda_nlreg() predict(<tda_nlreg>): Non-linear regression
tda_npreg(): Non-parametric regression
tda_zreg() tda_zreg1(): Regression with a censored response
tda_fml(): Maximum likelihood with a user-defined likelihood
tda_mlrc_design(): Design matrix for MLRC models
lvl(): A variable's value by category, for tda_qreg

Interval-valued data

tda_bounds(): Bounds from an interval regression
tda_icov() tda_icorr(): Covariance and correlation of interval-valued variables
tda_idf() tda_iddf(): Distribution function of an interval-valued variable
tda_imean() tda_ivariance() tda_igini(): Statistics of an interval-valued variable
tda_ilsreg(): Least squares with an interval-valued response
tda_imreg(): Conditional means with interval-valued data
tda_inpreg(): Non-parametric regression with interval-valued data
tda_isd(): Standard deviation of an interval-valued variable
tda_ivar(): Variance of an interval-valued variable (TDA's ivar)
tda_ivar1(): Variance of an interval-valued variable (TDA's ivar1)
tda_ivreg() tda_ivreg1() tda_ivreg2() tda_ivls(): Interval regression: a coefficient identified only up to bounds
tda_sddf(): Distribution function of a set-valued discrete variable
tda_evalfi(): Evaluate an inclusion function over an interval

Smoothing, interpolation and expressions

tda_sma(): Moving average
tda_smd(): Robust smoothing by running medians
tda_mwvec() tda_mwvec1(): Weighted mean of the later elements
tda_spl(): Smoothing spline
tda_interp(): Interpolate a surface over a grid
tda_isotonic(): Isotonic regression, with or without tie groups
tda_expand() tda_mparse(): Expand an expression, or parse a matrix expression

Optimization

Function evaluation, integration and minimisation; linear, quadratic and 0-1 programming; constrained least squares; assignment and location problems.

tda_integrate() tda_range() tda_evalf() tda_minimize() tda_gmin(): Integrate, minimise, and evaluate a function
tda_niset(): Numerical-integration settings
tda_mlp() tda_mlp1(): Linear programming
tda_mlpi(): 0-1 linear programming
tda_mls() tda_mlse() tda_mlsi() tda_mlsei() tda_mlsei1() tda_mnls(): Constrained least squares
tda_mqp() tda_mqpb() tda_mqpc(): Quadratic programming
tda_mqap(): Quadratic assignment problem
tda_gap(): The assignment problem
tda_gap_permute(): Column permutations toward graph agreement
tda_gqap(): Quadratic assignment (GRASP)
tda_locate_line(): One-dimensional multifacility location

Matrix algebra

TDA’s matrix commands, including the Leslie-matrix iteration it keeps among them.

tda_mat(): Matrix operations
tda_mag(): Aggregating a matrix by row and column groups
tda_mcath() tda_mcatv() tda_mcathv(): Concatenating matrices
tda_mcel(): Build an edge list from an adjacency-style matrix
tda_mcent() tda_mstand() tda_mdcent(): Centering, standardizing, and double-centering
tda_mch(): Check an ordering against row/column dominance
tda_mmul() tda_mtransp() tda_mchol(): Matrix multiplication, transposition, Cholesky decomposition
tda_mcross() tda_mnum(): Cross-product and an arithmetic sequence as a column
tda_mrsum() tda_mcsum() tda_mdrow() tda_mdcol(): Row and column sums, as vectors or diagonal matrices
tda_mcvec() tda_mrvec() tda_mivec(): Vectorizing a matrix and its inverse
tda_mdiag() tda_mdiagd(): Diagonal construction and extraction
tda_mev(): Eigen decomposition of a general (possibly non-symmetric) matrix
tda_mevs(): Eigen decomposition of a symmetric matrix
tda_eigen(): Eigenvalues of a matrix, via TDA
tda_minvs() tda_minvd() tda_mginv(): Matrix inversion
tda_mkp(): Kronecker product
tda_mnc(): Zero out matrix elements by a threshold test
tda_mnrow() tda_mncol() tda_mnorm() tda_mnorm1() tda_mnorm2() tda_mtrace(): Matrix size and norms
tda_mpbl() tda_mpbu(): Permute to block triangular form
tda_mpfit(): Iterative proportional fitting
tda_mpinv(): Invert a permutation
tda_mpit() tda_mpit1(): Iterate a Leslie matrix
tda_spmod(): Stationary solution of a Leslie matrix
tda_mpz(): Permute rows for a zero-free diagonal
tda_msort() tda_msort1() tda_mrank(): Sort or rank the rows of a matrix
tda_mscal1(): Scale a matrix by its total sum
tda_msqrtd() tda_msqrti(): Diagonal square root and its reciprocal
tda_msrow() tda_mscol() tda_mprow() tda_mpcol() tda_mpsym(): Selecting or permuting rows and columns
tda_msvd() tda_msvd1(): Singular value decomposition
tda_mtrim(): Trim or pad a matrix's edges

Clustering, scaling, rank-order and Boolean analysis

Cluster analysis, principal components and factor analysis, multidimensional scaling and unfolding, Procrustes rotation, conjoint, Rasch and rank-order methods, combinatorial patterns, Boolean functions.

TDA_CLUSTER tda_cluster(): Clustering from a dissimilarity matrix
tda_cutree(): Cut a dendrogram into groups
tda_clpyr(): Pyramidal clustering
tda_scla(): Separable clusters of a valued graph
tda_dma(): Principal components, factor analysis, correspondence analysis
tda_pdatd(): Distance matrix from raw variables
tda_dmet(): Convert a distance matrix into a metric
tda_dmet1(): Distances made metric
TDA_MDS tda_mds(): Multidimensional scaling
tda_mdsn(): Nonmetric multidimensional scaling
tda_mdsr(): Axes in an MDS configuration
tda_mproc(): Procrustes rotation
tda_unf(): Unfolding of preference data
tda_conjoint(): Non-metric conjoint analysis
tda_conj(): Conjoint analysis
tda_rmod(): Simple Rasch model
tda_sga(): Scalogram (Guttman) analysis
tda_rod(): Rank-order data utilities
tda_mkmet(): Kemeny distance between rankings
tda_rank_orders(): All rank orders of a given size
tda_com(): Combinatorial patterns
tda_pcyc(): Cycle structure of permutations
tda_bfc(): Context dependencies in Boolean functions
tda_boolean_min(): Boolean function minimization

Sequence analysis

tda_seq_info(): Information about currently defined sequence data structures
tda_seqgc() tda_seqlg() tda_seqsd() tda_seqsi() tda_seqen(): Sequence characteristics, lengths, gaps and state distributions
tda_seqm(): Sequence analysis by optimal matching
tda_seqmd() tda_seqev() tda_seqevd(): Regression models for events
tda_seqpd(): Write sequence data back out
tda_seqpe(): Derive a sequence data structure from episode data
tda_seqpm(): Sequence pattern matching

Graphs and networks

Graph objects and TDA’s graph analyses – components, paths, flows, cliques, trees, temporal networks.

tda_graph(): A graph for TDA's graph commands
tda_g(): Run a graph command
tda_g_components() tda_g_shortest() tda_g_mst() tda_g_cliques() tda_g_cycles() tda_g_cutpoints() tda_g_flow() tda_g_degrees() tda_g_edges() tda_g_transitive() tda_g_aggregate() tda_g_symmetric() tda_g_toposort() tda_g_nodes() tda_g_dot() tda_g_links() tda_g_dcycles() tda_g_dblocks() tda_g_compact() tda_g_gcliques() tda_g_random() tda_g_ownership() tda_g_backward() tda_g_paths() tda_g_flowcontrol() tda_g_centred() tda_g_spantrees() tda_g_reachable() tda_g_neighbourhoods() tda_g_independent() tda_g_spanning() tda_g_eigen(): Graph analyses
tda_gde(): Undirected graph from node lists
tda_gdu(): Union of two graphs
tda_gfcf(): Forward control flows in a directed graph
tda_ghd(): Hasse diagram of multivariate patterns
tda_gpro(): Projection of proximities
tda_mdefg(): Adjacency matrix of a graph
tda_rfit(): Fit binary relations to a valued graph
tda_tnet(): Temporal-network summaries
tda_ptree(): Print a tree's data structure
tda_ucl(): Split an ordering into contiguous clusters
plot(<tda_graph>): Draw a graph

Spatial data

tda_spatial(): Spatial data for TDA's spatial commands
tda_sd(): Run a spatial command
tda_sd_info() tda_sd_relations() tda_sd_neighbours() tda_sd_enclosing() tda_sd_voronoi() tda_sd_select() tda_sd_intersect() tda_sd_lines() tda_sd_points() tda_sd_data() tda_sd_clip(): Spatial analyses
tda_sd_ps3() tda_sd_pl3() tda_sd_pl3_points() tda_sd_pl3_lines() tda_sd_pl3_polygons() tda_sd_plot3() tda_sd_plot3_lines() tda_sd_plot3_polygons(): Three-dimensional spatial plots
tda_map(): Maps
tda_polygons(): Build polygons from line segments
tda_triang(): Triangulation of points
plot(<tda_spatial>): Draw spatial data

PostScript plotting

TDA’s plot commands, and reading the PostScript they write.

tda_ps(): A TDA plot
tda_ps3() tda_pl_points3() tda_pl_text3() tda_pl_surface3() tda_pl_curve3() tda_pl_lines3(): Three-dimensional plots
tda_pl() tda_pl_axes() tda_pl_frame() tda_pl_grid() tda_pl_lines() TDA_LTY tda_pl_points() tda_pl_smooth() tda_pl_circle() tda_pl_text() tda_pl_rect() tda_pl_polyline() tda_pl_function() tda_ps_file(): Add a command to a plot
tda_pl_arc(): Curved arcs
tda_pl_axis(): Draw a single axis, optionally at an explicit position
tda_pl_graph(): Draw a graph with explicit node positions
tda_pl_density() tda_pl_histogram() tda_pl_contour() tda_pl_curve() tda_pl_ellipse() tda_pl_labels() tda_pl_grid_lines(): Further plot commands
tda_pl_panel(): Start a new panel within the same session
tda_pl_regression() tda_pl_hull(): Add a fitted regression curve or convex hulls to a plot
tda_pl_scatter(): Scatterplots, sunflower plots, and lowess smoothing
tda_plotcm(): Contour plot of a matrix
tda_plotr(): Grey-scale relief of a matrix
tda_plotsp(): Akima-smoothed curve through points
tda_plcirc3(): Circle in a 3-d plot
tda_plglob3(): Globe in a 3-d plot
tda_plsurf3(): Parametric surface in a 3-d plot
tda_ps_objects(): What is inside a TDA PostScript file
tda_combine_ps(): Combine several PostScript plots into one file
tda_read_ps(): Read TDA's PostScript output
tda_plot_ps(): Draw TDA's PostScript output with grid
tda_check_ps(): Audit a parse against the PostScript it came from