G05 Chapter Contents (PDF version)
G05 Chapter Introduction
NAG Library Manual

NAG Library Chapter Contents

G05 – Random Number Generators


G05 Chapter Introduction – a description of the Chapter and an overview of the algorithms available

Routine
Name
Mark of
Introduction

Purpose
G05KFF
Example Text
Example Data
22 nagf_rand_init_repeat
Initializes a pseudorandom number generator to give a repeatable sequence
G05KGF
Example Text
22 nagf_rand_init_nonrepeat
Initializes a pseudorandom number generator to give a non-repeatable sequence
G05KHF
Example Text
Example Data
22 nagf_rand_init_leapfrog
Primes a pseudorandom number generator for generating multiple streams using leap-frog
G05KJF
Example Text
Example Data
22 nagf_rand_init_skipahead
Primes a pseudorandom number generator for generating multiple streams using skip-ahead
G05KKF
Example Text
Example Data
23 nagf_rand_init_skipahead_power2
Primes a pseudorandom number generator for generating multiple streams using skip-ahead, skipping ahead a power of 2
G05NCF
Example Text
Example Data
22 nagf_rand_permute
Pseudorandom permutation of an integer vector
G05NDF
Example Text
Example Data
22 nagf_rand_sample
Pseudorandom sample from an integer vector
G05NEF
Example Text
Example Data
23 nagf_rand_sample_wgt
Pseudorandom sample, without replacement, unequal weights
G05PDF
Example Text
Example Data
22 nagf_rand_times_garch_asym1
Generates a realization of a time series from a GARCH process with asymmetry of the form εt-1+γ2
G05PEF
Example Text
Example Data
22 nagf_rand_times_garch_asym2
Generates a realization of a time series from a GARCH process with asymmetry of the form εt-1+γ εt-12
G05PFF
Example Text
Example Data
22 nagf_rand_times_garch_GJR
Generates a realization of a time series from an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
G05PGF
Example Text
Example Data
22 nagf_rand_times_garch_exp
Generates a realization of a time series from an exponential GARCH (EGARCH) process
G05PHF
Example Text
Example Data
22 nagf_rand_times_arma
Generates a realization of a time series from an ARMA model
G05PJF
Example Text
Example Data
22 nagf_rand_times_mv_varma
Generates a realization of a multivariate time series from a VARMA model
G05PMF
Example Text
Example Data
Example Plot
22 nagf_rand_times_smooth_exp
Generates a realization of a time series from an exponential smoothing model
G05PVF
Example Text
Example Data
25 nagf_rand_kfold_xyw
Permutes a matrix, vector, vector triplet into a form suitable for K-fold cross validation
G05PWF
Example Text
Example Data
25 nagf_rand_subsamp_xyw
Permutes a matrix, vector, vector triplet into a form suitable for random sub-sampling validation
G05PXF
Example Text
Example Data
22 nagf_rand_matrix_orthog
Generates a random orthogonal matrix
G05PYF
Example Text
Example Data
22 nagf_rand_matrix_corr
Generates a random correlation matrix
G05PZF
Example Text
Example Data
22 nagf_rand_matrix_2waytable
Generates a random two-way table
G05RCF
Example Text
Example Data
22 nagf_rand_copula_students_t
Generates a matrix of pseudorandom numbers from a Student's t-copula
G05RDF
Example Text
Example Data
22 nagf_rand_copula_normal
Generates a matrix of pseudorandom numbers from a Gaussian copula
G05REF
Example Text
Example Data
23 nagf_rand_copula_clayton_bivar
Generates a matrix of pseudorandom numbers from a bivariate Clayton/Cook–Johnson copula
G05RFF
Example Text
Example Data
23 nagf_rand_copula_frank_bivar
Generates a matrix of pseudorandom numbers from a bivariate Frank copula
G05RGF
Example Text
Example Data
23 nagf_rand_copula_plackett_bivar
Generates a matrix of pseudorandom numbers from a bivariate Plackett copula
G05RHF
Example Text
Example Data
23 nagf_rand_copula_clayton
Generates a matrix of pseudorandom numbers from a multivariate Clayton/Cook–Johnson copula
G05RJF
Example Text
Example Data
23 nagf_rand_copula_frank
Generates a matrix of pseudorandom numbers from a multivariate Frank copula
G05RKF
Example Text
Example Data
23 nagf_rand_copula_gumbel
Generates a matrix of pseudorandom numbers from a Gumbel–Hougaard copula
G05RYF
Example Text
Example Data
22 nagf_rand_multivar_students_t
Generates a matrix of pseudorandom numbers from a multivariate Student's t-distribution
G05RZF
Example Text
Example Data
22 nagf_rand_multivar_normal
Generates a matrix of pseudorandom numbers from a multivariate Normal distribution
G05SAF
Example Text
Example Data
22 nagf_rand_dist_uniform01
Generates a vector of pseudorandom numbers from a uniform distribution over 0,1
G05SBF
Example Text
Example Data
22 nagf_rand_dist_beta
Generates a vector of pseudorandom numbers from a beta distribution
G05SCF
Example Text
Example Data
22 nagf_rand_dist_cauchy
Generates a vector of pseudorandom numbers from a Cauchy distribution
G05SDF
Example Text
Example Data
22 nagf_rand_dist_chisq
Generates a vector of pseudorandom numbers from a χ2 distribution
G05SEF
Example Text
Example Data
22 nagf_rand_dist_dirichlet
Generates a vector of pseudorandom numbers from a Dirichlet distribution
G05SFF
Example Text
Example Data
22 nagf_rand_dist_exp
Generates a vector of pseudorandom numbers from an exponential distribution
G05SGF
Example Text
Example Data
22 nagf_rand_dist_expmix
Generates a vector of pseudorandom numbers from an exponential mix distribution
G05SHF
Example Text
Example Data
22 nagf_rand_dist_f
Generates a vector of pseudorandom numbers from an F-distribution
G05SJF
Example Text
Example Data
22 nagf_rand_dist_gamma
Generates a vector of pseudorandom numbers from a gamma distribution
G05SKF
Example Text
Example Data
22 nagf_rand_dist_normal
Generates a vector of pseudorandom numbers from a Normal distribution
G05SLF
Example Text
Example Data
22 nagf_rand_dist_logistic
Generates a vector of pseudorandom numbers from a logistic distribution
G05SMF
Example Text
Example Data
22 nagf_rand_dist_lognormal
Generates a vector of pseudorandom numbers from a log-normal distribution
G05SNF
Example Text
Example Data
22 nagf_rand_dist_students_t
Generates a vector of pseudorandom numbers from a Student's t-distribution
G05SPF
Example Text
Example Data
22 nagf_rand_dist_triangular
Generates a vector of pseudorandom numbers from a triangular distribution
G05SQF
Example Text
Example Data
22 nagf_rand_dist_uniform
Generates a vector of pseudorandom numbers from a uniform distribution over a,b
G05SRF
Example Text
Example Data
22 nagf_rand_dist_vonmises
Generates a vector of pseudorandom numbers from a von Mises distribution
G05SSF
Example Text
Example Data
22 nagf_rand_dist_weibull
Generates a vector of pseudorandom numbers from a Weibull distribution
G05TAF
Example Text
Example Data
22 nagf_rand_int_binomial
Generates a vector of pseudorandom integers from a binomial distribution
G05TBF
Example Text
Example Data
22 nagf_rand_logical
Generates a vector of pseudorandom logical values
G05TCF
Example Text
Example Data
22 nagf_rand_int_geom
Generates a vector of pseudorandom integers from a geometric distribution
G05TDF
Example Text
Example Data
22 nagf_rand_int_general
Generates a vector of pseudorandom integers from a general discrete distribution
G05TEF
Example Text
Example Data
22 nagf_rand_int_hypergeom
Generates a vector of pseudorandom integers from a hypergeometric distribution
G05TFF
Example Text
Example Data
22 nagf_rand_int_log
Generates a vector of pseudorandom integers from a logarithmic distribution
G05TGF
Example Text
Example Data
22 nagf_rand_int_multinomial
Generates a vector of pseudorandom integers from a multinomial distribution
G05THF
Example Text
Example Data
22 nagf_rand_int_negbin
Generates a vector of pseudorandom integers from a negative binomial distribution
G05TJF
Example Text
Example Data
22 nagf_rand_int_poisson
Generates a vector of pseudorandom integers from a Poisson distribution
G05TKF
Example Text
Example Data
22 nagf_rand_int_poisson_varmean
Generates a vector of pseudorandom integers from a Poisson distribution with varying mean
G05TLF
Example Text
Example Data
22 nagf_rand_int_uniform
Generates a vector of pseudorandom integers from a uniform distribution
G05XAF
Example Text
24 nagf_rand_bb_init
Initializes the Brownian bridge generator
G05XBF
Example Text
24 nagf_rand_bb
Generate paths for a free or non-free Wiener process using the Brownian bridge algorithm
G05XCF
Example Text
24 nagf_rand_bb_inc_init
Initializes the generator which backs out the increments of sample paths generated by a Brownian bridge algorithm
G05XDF
Example Text
24 nagf_rand_bb_inc
Backs out the increments from sample paths generated by a Brownian bridge algorithm
G05XEF
Example Text
24 nagf_rand_bb_make_bridge_order
Creates a Brownian bridge construction order out of a set of input times
G05YJF
Example Text
Example Data
21 nagf_rand_quasi_normal
Generates a Normal quasi-random number sequence
G05YKF
Example Text
Example Data
21 nagf_rand_quasi_lognormal
Generates a log-normal quasi-random number sequence
G05YLF 22 nagf_rand_quasi_init
Initializes a quasi-random number generator
G05YMF
Example Text
Example Data
22 nagf_rand_quasi_uniform
Generates a uniform quasi-random number sequence
G05YNF
Example Text
Example Data
22 nagf_rand_quasi_init_scrambled
Initializes a scrambled quasi-random number generator
G05ZMF
Example Text
Example Data
24 nagf_rand_field_1d_user_setup
Setup for simulating one-dimensional random fields, user-defined variogram
G05ZNF
Example Text
Example Data
24 nagf_rand_field_1d_predef_setup
Setup for simulating one-dimensional random fields
G05ZPF
Example Text
Example Data
24 nagf_rand_field_1d_generate
Generates realizations of a one-dimensional random field
G05ZQF
Example Text
Example Data
24 nagf_rand_field_2d_user_setup
Setup for simulating two-dimensional random fields, user-defined variogram
G05ZRF
Example Text
Example Data
Example Plot
24 nagf_rand_field_2d_predef_setup
Setup for simulating two-dimensional random fields, preset variogram
G05ZSF
Example Text
Example Data
24 nagf_rand_field_2d_generate
Generates realizations of a two-dimensional random field
G05ZTF
Example Text
Example Data
24 nagf_rand_field_fracbm_generate
Generates realizations of fractional Brownian motion

G05 Chapter Contents (PDF version)
G05 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2016