GAMS: Problem Taxonomy

Classes

GAMS	Classification Scheme
A	Arithmetic, error analysis
A1	Integer
A2	Rational
A3	Real
A3a	Standard precision
A3c	Extended precision
A3d	Extended range
A4	Complex
A4a	Standard precision
A4c	Extended precision
A4d	Extended range
A5	Interval
A6	Change of representation
A6a	Type conversion
A6b	Base conversion
A6c	Decomposition, construction
A7	Sequences (e.g., convergence acceleration)
B	Number theory
C	Elementary and special functions
C1	Integer-valued functions (e.g., factorial, binomial coefficient, permutations, combinations, floor, ceiling)
C2	Powers, roots, reciprocals
C3	Polynomials
C3a	Orthogonal
C3a1	Trigonometric
C3a2	Chebyshev, Legendre
C3a3	Laguerre
C3a4	Hermite
C3b	Non-orthogonal
C4	Elementary transcendental functions
C4a	Trigonometric, inverse trigonometric
C4b	Exponential, logarithmic
C4c	Hyperbolic, inverse hyperbolic
C4d	Integrals of elementary transcendental functions
C5	Exponential and logarithmic integrals
C6	Cosine and sine integrals
C7	Gamma
C7a	Gamma, log gamma, reciprocal gamma
C7b	Beta, log beta
C7c	Psi function
C7d	Polygamma function
C7e	Incomplete gamma
C7f	Incomplete beta
C7g	Riemann zeta
C8	Error functions
C8a	Error functions, their inverses, integrals, including the normal distribution function
C8b	Fresnel integrals
C8c	Dawson''s integral
C9	Legendre functions
C10	Bessel functions
C10a	J, Y, H-(1), H-(2)
C10a1	Real argument, integer order
C10a2	Complex argument, integer order
C10a3	Real argument, real order
C10a4	Complex argument, real order
C10a5	Complex argument, complex order
C10b	I, K
C10b1	Real argument, integer order
C10b2	Complex argument, integer order
C10b3	Real argument, real order
C10b4	Complex argument, real order
C10b5	Complex argument, complex order
C10c	Kelvin functions
C10d	Airy and Scorer functions
C10e	Struve, Anger, and Weber functions
C10f	Integrals of Bessel functions
C11	Confluent hypergeometric functions
C12	Coulomb wave functions
C13	Jacobian elliptic functions, theta functions
C14	Elliptic integrals
C15	Weierstrass elliptic functions
C16	Parabolic cylinder functions
C17	Mathieu functions
C18	Spheroidal wave functions
C19	Other special functions
D	Linear Algebra
D1	Elementary vector and matrix operations
D1a	Elementary vector operations
D1a1	Set to constant
D1a2	Minimum and maximum components
D1a3	Norm
D1a3a	L-1 (sum of magnitudes)
D1a3b	L-2 (Euclidean norm)
D1a3c	L-infinity (maximum magnitude)
D1a4	Dot product (inner product)
D1a5	Copy or exchange (swap)
D1a6	Multiplication by scalar
D1a7	Triad (a*x+y for vectors x,y and scalar a)
D1a8	Elementary rotation (Givens transformation)
D1a9	Elementary reflection (Householder transformation)
D1a10	Convolutions
D1a11	Other vector operations
D1b	Elementary matrix operations
D1b1	Initialize (e.g., to zero or identity)
D1b2	Norm
D1b3	Transpose
D1b4	Multiplication by vector
D1b5	Addition, subtraction
D1b6	Multiplication
D1b7	Matrix polynomial
D1b8	Copy
D1b9	Storage mode conversion
D1b10	Elementary rotation (Givens transformation)
D1b11	Elementary reflection (Householder transformation)
D2	Solution of systems of linear equations (including inversion, LU and related decompositions)
D2a	Real nonsymmetric matrices
D2a1	General
D2a2	Banded
D2a2a	Tridiagonal
D2a3	Triangular
D2a4	Sparse
D2b	Real symmetric matrices
D2b1	General
D2b1a	Indefinite
D2b1b	Positive definite
D2b2	Positive definite banded
D2b2a	Tridiagonal
D2b4	Sparse
D2c	Complex non-Hermitian matrices
D2c1	General
D2c2	Banded
D2c2a	Tridiagonal
D2c3	Triangular
D2c4	Sparse
D2d	Complex Hermitian matrices
D2d1	General
D2d1a	Indefinite
D2d1b	Positive definite
D2d2	Positive definite banded
D2d2a	Tridiagonal
D2d4	Sparse
D2e	Associated operations (e.g., matrix reorderings)
D3	Determinants
D3a	Real nonsymmetric matrices
D3a1	General
D3a2	Banded
D3a2a	Tridiagonal
D3a3	Triangular
D3a4	Sparse
D3b	Real symmetric matrices
D3b1	General
D3b1a	Indefinite
D3b1b	Positive definite
D3b2	Positive definite banded
D3b2a	Tridiagonal
D3b4	Sparse
D3c	Complex non-Hermitian matrices
D3c1	General
D3c2	Banded
D3c2a	Tridiagonal
D3c3	Triangular
D3c4	Sparse
D3d	Complex Hermitian matrices
D3d1	General
D3d1a	Indefinite
D3d1b	Positive definite
D3d2	Positive definite banded
D3d2a	Tridiagonal
D3d4	Sparse
D4	Eigenvalues, eigenvectors
D4a	Ordinary eigenvalue problems (Ax = (lambda) * x)
D4a1	Real symmetric
D4a2	Real nonsymmetric
D4a3	Complex Hermitian
D4a4	Complex non-Hermitian
D4a5	Tridiagonal
D4a6	Banded
D4a7	Sparse
D4b	Generalized eigenvalue problems (e.g., Ax = (lambda)*Bx)
D4b1	Real symmetric
D4b2	Real general
D4b3	Complex Hermitian
D4b4	Complex general
D4b5	Banded
D4c	Associated operations
D4c1	Transform problem
D4c1a	Balance matrix
D4c1b	Reduce to compact form
D4c1b1	Tridiagonal
D4c1b2	Hessenberg
D4c1b3	Other
D4c1c	Standardize problem
D4c2	Compute eigenvalues of matrix in compact form
D4c2a	Tridiagonal
D4c2b	Hessenberg
D4c2c	Other
D4c3	Form eigenvectors from eigenvalues
D4c4	Back transform eigenvectors
D4c5	Determine Jordan normal form
D5	QR decomposition, Gram-Schmidt orthogonalization
D6	Singular value decomposition
D7	Update matrix decompositions
D7a	LU
D7b	Cholesky
D7c	QR
D7d	Singular value
D8	Other matrix equations (e.g., AX+XB=C)
D9	Singular, overdetermined or underdetermined systems of linear equations, generalized inverses
D9a	Unconstrained
D9a1	Least squares (L-2) solution
D9a2	Chebyshev (L-infinity) solution
D9a3	Least absolute value (L-1) solution
D9a4	Other
D9b	Constrained
D9b1	Least squares (L-2) solution
D9b2	Chebyshev (L-infinity) solution
D9b3	Least absolute value (L-1)
D9b4	Other
D9c	Generalized inverses
E	Interpolation
E1	Univariate data (curve fitting)
E1a	Polynomial splines (piecewise polynomials)
E1b	Polynomials
E1c	Other functions (e.g., rational, trigonometric)
E2	Multivariate data (surface fitting)
E2a	Gridded
E2b	Scattered
E3	Service routines for interpolation
E3a	Evaluation of fitted functions, including quadrature
E3a1	Function evaluation
E3a2	Derivative evaluation
E3a3	Quadrature
E3b	Grid or knot generation
E3c	Manipulation of basis functions (e.g., evaluation, change of basis)
E3d	Other
F	Solution of nonlinear equations
F1	Single equation
F1a	Polynomial
F1a1	Real coefficients
F1a2	Complex coefficients
F1b	Nonpolynomial
F2	System of equations
F3	Service routines (e.g., check user-supplied derivatives)
G	Optimization
G1	Unconstrained
G1a	Univariate
G1a1	Smooth function
G1a1a	User provides no derivatives
G1a1b	User provides first derivatives
G1a1c	User provides first and second derivatives
G1a2	General function (no smoothness assumed)
G1b	Multivariate
G1b1	Smooth function
G1b1a	User provides no derivatives
G1b1b	User provides first derivatives
G1b1c	User provides first and second derivatives
G1b2	General function (no smoothness assumed)
G2	Constrained
G2a	Linear programming
G2a1	Dense matrix of constraints
G2a2	Sparse matrix of constraints
G2b	Transportation and assignments problem
G2c	Integer programming
G2c1	Zero/one
G2c2	Covering and packing problems
G2c3	Knapsack problems
G2c4	Matching problems
G2c5	Routing, scheduling, location problems
G2c6	Pure integer programming
G2c7	Mixed integer programming
G2d	Network
G2d1	Shortest path
G2d2	Minimum spanning tree
G2d3	Maximum flow
G2d3a	Generalized networks
G2d3b	Networks with side constraints
G2d4	Test problem generation
G2e	Quadratic programming
G2e1	Positive definite Hessian (i.e., convex problem)
G2e2	Indefinite Hessian
G2f	Geometric programming
G2g	Dynamic programming
G2h	General nonlinear programming
G2h1	Simple bounds
G2h1a	Smooth function
G2h1a1	User provides no derivatives
G2h1a2	User provides first derivatives
G2h1a3	User provides first and second derivatives
G2h1b	General function (no smoothness assumed)
G2h2	Linear equality or inequality constraints
G2h2a	Smooth function
G2h2a1	User provides no derivatives
G2h2a2	User provides first derivatives
G2h2a3	User provides first and second derivatives
G2h2b	General function (no smoothness assumed)
G2h3	Nonlinear constraints
G2h3a	Equality constraints only
G2h3a1	Smooth function and constraints
G2h3a1a	User provides no derivatives
G2h3a1b	User provides first derivatives of function and constraints
G2h3a1c	User provides first and second derivatives of function and constraints
G2h3a2	General function and constraints (no smoothness assumed)
G2h3b	Equality and inequality constraints
G2h3b1	Smooth function and constraints
G2h3b1a	User provides no derivatives
G2h3b1b	User provides first derivatives of function and constraints
G2h3b1c	User provides first and second derivatives of function and constraints
G2h3b2	General function and constraints (no smoothness assumed)
G2i	Global solution to nonconvex problems
G3	Optimal control
G4	Service routines
G4a	Problem input (e.g., matrix generation)
G4b	Problem scaling
G4c	Check user-supplied derivatives
G4d	Find feasible point
G4e	Check for redundancy
G4f	Other
H	Differentiation, integration
H1	Numerical differentiation
H2	Quadrature (numerical evaluation of definite integrals)
H2a	One-dimensional integrals
H2a1	Finite interval (general integrand)
H2a1a	Integrand available via user-defined procedure
H2a1a1	Automatic (user need only specify required accuracy)
H2a1a2	Nonautomatic
H2a1b	Integrand available only on grid
H2a1b1	Automatic (user need only specify required accuracy)
H2a1b2	Nonautomatic
H2a2	Finite interval (specific or special type integrand including weight functions, oscillating and singular integrands, principal value integrals, splines, etc.)
H2a2a	Integrand available via user-defined procedure
H2a2a1	Automatic (user need only specify required accuracy)
H2a2a2	Nonautomatic
H2a2b	Integrand available only on grid
H2a2b1	Automatic (user need only specify required accuracy)
H2a2b2	Nonautomatic
H2a3	Semi-infinite interval (including exp(-x) weight function)
H2a3a	Integrand available via user-defined procedure
H2a3a1	Automatic (user need only specify required accuracy)
H2a3a2	Nonautomatic
H2a4	Infinite interval (including exp(-x**2) weight function)
H2a4a	Integrand available via user-defined procedure
H2a4a1	Automatic (user need only specify required accuracy)
H2a4a2	Nonautomatic
H2b	Multidimensional integrals
H2b1	One or more hyper-rectangular regions (includes iterated integrals)
H2b1a	Integrand available via user-defined procedure
H2b1a1	Automatic (user need only specify required accuracy)
H2b1a2	Nonautomatic
H2b1b	Integrand available only on grid
H2b1b1	Automatic (user need only specify required accuracy)
H2b1b2	Nonautomatic
H2b2	n-dimensional quadrature on a nonrectangular region
H2b2a	Integrand available via user-defined procedure
H2b2a1	Automatic (user need only specify required accuracy)
H2b2a2	Nonautomatic
H2b2b	Integrand available only on grid
H2b2b1	Automatic (user need only specify required accuracy)
H2b2b2	Nonautomatic
H2c	Service routines (e.g., compute weights and nodes for quadrature formulas)
I	Differential and integral equations
I1	Ordinary differential equations (ODE''s)
I1a	Initial value problems
I1a1	General, nonstiff or mildly stiff
I1a1a	One-step methods (e.g., Runge-Kutta)
I1a1b	Multistep methods (e.g., Adams predictor-corrector)
I1a1c	Extrapolation methods (e.g., Bulirsch-Stoer)
I1a2	Stiff and mixed algebraic- differential equations
I1b	Multipoint boundary value problems
I1b1	Linear
I1b2	Nonlinear
I1b3	Eigenvalue (e.g., Sturm-Liouville)
I1c	Service routines (e.g., interpolation of solutions, error handling, test programs)
I2	Partial differential equations
I2a	Initial boundary value problems
I2a1	Parabolic
I2a1a	One spatial dimension
I2a1b	Two or more spatial dimensions
I2a2	Hyperbolic
I2b	Elliptic boundary value problems
I2b1	Linear
I2b1a	Second order
I2b1a1	Poisson (Laplace) or Helmholtz equation
I2b1a1a	Rectangular domain (or topologically rectangular in the coordinate system)
I2b1a1b	Nonrectangular domain
I2b1a2	Other separable problems
I2b1a3	Nonseparable problems
I2b1c	Higher order equations (e.g., biharmonic)
I2b2	Nonlinear
I2b3	Eigenvalue
I2b4	Service routines
I2b4a	Domain triangulation
I2b4b	Solution of discretized elliptic equations
I3	Integral equations
J	Integral transforms
J1	Trigonometric transforms including fast Fourier transforms
J1a	One-dimensional
J1a1	Real
J1a2	Complex
J1a3	Sine and cosine transforms
J1b	Multidimensional
J2	Convolutions
J3	Laplace transforms
J4	Hilbert transforms
K	Approximation
K1	Least squares (L-2) approximation
K1a	Linear least squares
K1a1	Unconstrained
K1a1a	Univariate data (curve fitting)
K1a1a1	Polynomial splines (piecewise polynomials)
K1a1a2	Polynomials
K1a1a3	Other functions (e.g., trigonometric, user-specified)
K1a1b	Multivariate data (surface fitting)
K1a2	Constrained
K1a2a	Linear constraints
K1a2b	Nonlinear constraints
K1b	Nonlinear least squares
K1b1	Unconstrained
K1b1a	Smooth functions
K1b1a1	User provides no derivatives
K1b1a2	User provides first derivatives
K1b1a3	User provides first and second derivatives
K1b1b	General functions
K1b2	Constrained
K1b2a	Linear constraints
K1b2b	Nonlinear constraints
K2	Minimax (L-infinity) approximation
K3	Least absolute value (L-1) approximation
K4	Other analytic approximations (e.g., Taylor polynomial, Pade)
K5	Smoothing
K6	Service routines for approximation
K6a	Evaluation of fitted functions, including quadrature
K6a1	Function evaluation
K6a2	Derivative evaluation
K6a3	Quadrature
K6b	Grid or knot generation
K6c	Manipulation of basis functions (e.g., evaluation, change of basis)
K6d	Other
L	Statistics, probability
L1	Data summarization
L1a	One-dimensional data
L1a1	Raw data
L1a1a	Location
L1a1b	Dispersion
L1a1c	Shape
L1a1d	Frequency, cumulative frequency
L1a1e	Ties
L1a3	Grouped data
L1b	Two dimensional data
L1c	Multi-dimensional data
L1c1	Raw data
L1c1b	Covariance, correlation
L1c1d	Frequency, cumulative frequency
L1c2	Raw data containing missing values
L2	Data manipulation
L2a	Transform
L2b	Tally
L2c	Subset
L2d	Merge
L2e	Construct new variables (e.g., indicator variables)
L3	Elementary statistical graphics
L3a	One-dimensional data
L3a1	Histograms
L3a2	Frequency, cumulative frequency, percentile plots
L3a3	EDA (e.g., box-plots)
L3a4	Bar charts
L3a5	Pie charts
L3a6	X(i) vs. i (including symbol plots)
L3a7	Lag plots (e.g., plots of X(i) vs. X(i-1))
L3b	Two-dimensional data
L3b1	Histograms (superimposed and bivariate)
L3b2	Frequency, cumulative frequency
L3b3	Scatter diagrams
L3b3a	Y vs. X
L3b3b	Symbol plots
L3b3c	Lag plots (i.e., plots of X(i) vs. Y(i-j))
L3b4	EDA
L3c	Three-dimensional data
L3e	Multi-dimensional data
L3e1	Histograms
L3e2	Frequency, cumulative frequency, percentile plots
L3e3	Scatter diagrams
L3e3a	Superimposed Y vs. X
L3e3c	Superimposed X(i) vs. i
L3e3d	Matrices of bivariate scatter diagrams
L3e4	EDA
L4	Elementary data analysis
L4a	One-dimensional data
L4a1	Raw data
L4a1a	Parametric analysis
L4a1a1	Plots of empirical and theoretical density and distribution functions
L4a1a2	Probability plots
L4a1a2b	Beta, binomial
L4a1a2c	Cauchy, chi-squared
L4a1a2d	Double exponential
L4a1a2e	Exponential, extreme value
L4a1a2f	F distribution
L4a1a2g	Gamma, geometric
L4a1a2h	Halfnormal
L4a1a2l	Lambda, logistic, lognormal
L4a1a2n	Negative binomial, normal
L4a1a2p	Pareto, Poisson
L4a1a2s	Semicircular
L4a1a2t	t distribution, triangular
L4a1a2u	Uniform
L4a1a2w	Weibull
L4a1a3	Probability plot correlation coefficient plots
L4a1a3c	Chi-squared
L4a1a3e	Extreme value
L4a1a3g	Gamma, geometric
L4a1a3l	Lambda
L4a1a3n	Normal
L4a1a3p	Pareto, Poisson
L4a1a3t	t distribution
L4a1a3w	Weibull
L4a1a4	Parameter estimates and tests
L4a1a4b	Binomial
L4a1a4e	Extreme value
L4a1a4n	Normal
L4a1a4p	Poisson
L4a1a4u	Uniform
L4a1a4w	Weibull
L4a1a5	Transformation selection (e.g., for normality)
L4a1a6	Tail and outlier analysis
L4a1a7	Tolerance limits
L4a1b	Nonparametric analysis
L4a1b1	Estimates and tests regarding location (e.g., median), dispersion, and shape
L4a1b2	Density function estimation
L4a1c	Goodness-of-fit tests
L4a1d	Analysis of a sequence of numbers
L4a3	Grouped and/or censored data
L4a4	Data sampled from a finite population
L4a5	Categorical data
L4b	Two dimensional data
L4b1	Pairwise independent data
L4b1a	Parametric analysis
L4b1a1	Plots of empirical and theoretical density and distribution functions
L4b1a4	Parameter estimates and hypothesis tests
L4b1b	Nonparametric analysis (e.g., rank tests)
L4b1c	Goodness-of-fit tests
L4b3	Pairwise dependent data
L4b4	Pairwise dependent grouped data
L4b5	Data sampled from a finite population
L4c	Multi-dimensional data
L4c1	Independent data
L4c1a	Parametric analysis
L4c1b	Nonparametric analysis
L4e	Multiple multi-dimensional data sets
L5	Function evaluation
L5a	Univariate
L5a1	Cumulative distribution functions, probability density functions
L5a1b	Beta, binomial
L5a1c	Cauchy, chi-squared
L5a1d	Double exponential
L5a1e	Error function, exponential, extreme value
L5a1f	F distribution
L5a1g	Gamma, general, geometric
L5a1h	Halfnormal, hypergeometric
L5a1k	Kendall F statistic, Kolmogorov-Smirnov
L5a1l	Lambda, logistic, lognormal
L5a1n	Negative binomial, normal
L5a1p	Pareto, Poisson
L5a1t	t distribution
L5a1u	Uniform
L5a1v	Von Mises
L5a1w	Weibull
L5a2	Inverse distribution functions, sparsity functions
L5a2b	Beta, binomial
L5a2c	Cauchy, chi-squared
L5a2d	Double exponential
L5a2e	Error function, exponential, extreme value
L5a2f	F distribution
L5a2g	Gamma, general, geometric
L5a2h	Halfnormal
L5a2l	Lambda, logistic, lognormal
L5a2n	Negative binomial, normal, normal order statistics
L5a2p	Pareto, Poisson
L5a2t	t distribution
L5a2u	Uniform
L5a2w	Weibull
L5b	Multivariate
L5b1	Cumulative multivariate distribution functions, probability density functions
L5b1n	Normal
L5b2	Inverse cumulative distribution functions
L5b2n	Normal
L6	Random number generation
L6a	Univariate
L6a2	Beta, binomial, Boolean
L6a3	Cauchy, chi-squared
L6a4	Double exponential
L6a5	Exponential, extreme value
L6a6	F distribution
L6a7	Gamma, general (continuous, discrete), geometric
L6a8	Halfnormal, hypergeometric
L6a12	Lambda, logistic, lognormal
L6a14	Negative binomial, normal, normal order statistics
L6a16	Pareto, Pascal, permutations, Poisson
L6a19	Samples, stable distribution
L6a20	t distribution, time series, triangular
L6a21	Uniform (continuous, discrete), uniform order statistics
L6a22	Von Mises
L6a23	Weibull
L6b	Multivariate
L6b3	Contingency table, correlation matrix
L6b5	Experimental designs
L6b12	Linear L-1 (least absolute value) approximation
L6b13	Multinomial
L6b14	Normal
L6b15	Orthogonal matrix
L6b21	Uniform
L6c	Service routines (e.g., seed)
L7	Analysis of variance (including analysis of covariance)
L7a	One-way
L7a1	Parametric
L7a2	Nonparametric
L7b	Two-way
L7c	Three-way (e.g., Latin squares)
L7d	Multi-way
L7d1	Balanced complete data (e.g., factorial designs)
L7d2	Balanced incomplete data
L7d3	General linear models (unbalanced data)
L7e	Multivariate
L7f	Generate experimental designs
L7g	Service routines
L8	Regression
L8a	Simple linear (i.e., y = b(0) + b(1)*x)
L8a1	Ordinary least squares
L8a1a	Parameter estimation
L8a1a1	Unweighted data
L8a1a2	Weighted data
L8a1d	Inference (e.g., calibration)
L8a2	L-p for p different from 2 (e.g., least absolute value, minimax)
L8a3	Robust
L8a4	Errors in variables
L8b	Polynomial (e.g., y = b(0) + b(1)x + b(2)x**2)
L8b1	Ordinary least squares
L8b1a	Degree determination
L8b1b	Parameter estimation
L8b1b1	Not using orthogonal polynomials
L8b1b2	Using orthogonal polynomials
L8b1c	Analysis
L8b1d	Inference
L8c	Multiple linear (i.e., y = b(0) + b(1)x(1) + ... + b(p)x(p))
L8c1	Ordinary least squares
L8c1a	Variable selection
L8c1a1	Using raw data
L8c1a2	Using correlation or covariance data
L8c1a3	Using other data
L8c1b	Parameter estimation
L8c1b1	Using raw data
L8c1b2	Using correlation data
L8c1c	Analysis
L8c1d	Inference
L8c2	Several regressions
L8c3	L-p for p different from 2
L8c4	Robust
L8c5	Measurement error models
L8c6	Models based on ranks
L8d	Polynomial in several variables
L8e	Nonlinear (i.e., y = F(X,b))
L8e1	Ordinary least squares
L8e1a	Variable selection
L8e1b	Parameter estimation
L8e1b1	Unweighted data, user provides no derivatives
L8e1b2	Unweighted data, user provides derivatives
L8e1b3	Weighted data, user provides no derivatives
L8e1b4	Weighted data, user provides derivatives
L8e2	Ridge
L8e5	Measurement error models
L8f	Simultaneous (i.e., Y = Xb)
L8g	Spline (i.e., piecewise polynomial)
L8h	EDA (e.g., smoothing)
L8i	Service routines (e.g., matrix manipulation for variable selection)
L9	Categorical data analysis
L9a	2-by-2 tables
L9b	Two-way tables
L9c	Log-linear model
L9d	EDA (e.g., median polish)
L10	Time series analysis
L10a	Univariate
L10a1	Transformations
L10a1a	Elementary
L10a1b	Stationarity
L10a1c	Filters
L10a1c1	Difference
L10a1c2	Symmetric linear (e.g., moving averages)
L10a1c3	Autoregressive linear
L10a1c4	Other
L10a1d	Taper
L10a2	Time domain analysis
L10a2a	Summary statistics
L10a2a1	Autocorrelations and autocovariances
L10a2a2	Partial autocorrelations
L10a2b	Stationarity analysis
L10a2c	Autoregressive models
L10a2c1	Model identification
L10a2c2	Parameter estimation
L10a2d	ARMA and ARIMA models (including Box-Jenkins methods)
L10a2d1	Model identification
L10a2d2	Parameter estimation
L10a2d3	Forecasting
L10a2e	State-space analysis (e.g., Kalman filtering)
L10a2f	Analysis of a locally stationary series
L10a3	Frequency domain analysis
L10a3a	Spectral analysis
L10a3a1	Pilot analysis
L10a3a2	Periodogram analysis
L10a3a3	Spectrum estimation using the periodogram
L10a3a4	Spectrum estimation using the Fourier transform of the autocorrelation function
L10a3a5	Spectrum estimation using autoregressive models
L10a3a6	Spectral windows
L10a3b	Complex demodulation
L10b	Two time series
L10b2	Time domain analysis
L10b2a	Summary statistics (e.g., cross-correlations)
L10b2b	Transfer function models
L10b3	Frequency domain analysis
L10b3a	Cross-spectral analysis
L10b3a2	Cross-periodogram analysis
L10b3a3	Cross-spectrum estimation using the cross-periodogram
L10b3a4	Cross-spectrum estimation using the Fourier transform of the cross-correlation or cross-covariance function
L10b3a6	Spectral functions
L10c	Multivariate time series
L10d	Two multi-channel time series
L11	Correlation analysis
L12	Discriminant analysis
L13	Covariance structure models
L13a	Factor analysis
L13b	Principal components analysis
L13c	Canonical correlation
L14	Cluster analysis
L14a	One-way
L14a1	Unconstrained
L14a1a	Nested
L14a1a1	Joining (e.g., single link)
L14a1a2	Divisive
L14a1a3	Switching
L14a1a4	Predict missing values
L14a1b	Non-nested (e.g., K means)
L14a2	Constrained
L14b	Two-way
L14c	Display
L14d	Service routines (e.g., compute distance matrix)
L15	Life testing, survival analysis
L16	Multidimensional scaling
L17	Statistical data sets
M	Simulation, stochastic modeling
M1	Simulation
M1a	Discrete
M1b	Continuous (Markov models)
M2	Queueing
M3	Reliability
M3a	Quality control
M3b	Electrical network
M4	Project optimization (e.g., PERT)
N	Data handling
N1	Input, output
N2	Bit manipulation
N3	Character manipulation
N4	Storage management (e.g., stacks, heaps, trees)
N5	Searching
N5a	Extreme value
N5b	Insertion position
N5c	On a key
N6	Sorting
N6a	Internal
N6a1	Passive (i.e. construct pointer array, rank)
N6a1a	Integer
N6a1b	Real
N6a1c	Character
N6a2	Active
N6a2a	Integer
N6a2b	Real
N6a2c	Character
N6b	External
N7	Merging
N8	Permuting
O	Symbolic computation
P	Computational geometry
Q	Graphics
R	Service routines
R1	Machine-dependent constants
R2	Error checking (e.g., check monotonicity)
R3	Error handling
R3a	Set criteria for fatal errors
R3b	Set unit number for error messages
R3c	Other utilities
R4	Documentation retrieval
S	Software development tools
S1	Program transformation tools
S2	Static program analysis tools
S3	Dynamic program analysis tools
Z	Other
Unclassified	Unclassified