ParaMonte Fortran 2.0.0
Parallel Monte Carlo and Machine Learning Library
See the latest version documentation.
pm_distCov::getCovRand Interface Reference

Generate and return a random positive-definite (correlation or covariance) matrix using the Gram method.
More...

Detailed Description

Generate and return a random positive-definite (correlation or covariance) matrix using the Gram method.

See the documentation of pm_distCov for details.
See also setCovRand for generating random covariance matrices using the method of Dvine or Onion.

Parameters
[in]mold: The input scalar of,
  1. type complex of kind any supported by the processor (e.g., CK, CK32, CK64, or CK128),
  2. type real of kind any supported by the processor (e.g., RK, RK32, RK64, or RK128),
whose type and kind determines the type and kind of the output rand.
The value of mold is ignored entirely within the algorithm.
[in]ndim: The input positive scalar of type integer of default kind IK, representing the rank of the matrix (the number of dimensions) of shape (ndim, ndim).
(optional. It must be present if and only if the input scale argument is missing or is a scalar.)
[in]scale: The input scalar or contiguous vector of size ndim of type real of the same kind as the output argument rand, representing the scale of the matrix (e.g., the standard deviation of a covariance matrix) along each dimension.
(optional. default = 1.. It can be present if and only if it is a scalar or, it is a vector and the input argument ndim is missing.)
Returns
rand : The output matrix of shape (1:ndim, 1:ndim) of the same type and kind as the input argument mold, containing a random positive-definite matrix.


Possible calling interfaces ⛓

use pm_distCov, only: getCovRand
rand(1:ndim, 1:ndim) = getCovRand(mold, scale(1:ndim))
rand(1:ndim, 1:ndim) = getCovRand(mold, ndim, scale = scale)
pm_distCov::getCovRand
Generate and return a random positive-definite (correlation or covariance) matrix using the Gram meth...
Definition: pm_distCov.F90:394
pm_distCov
This module contains classes and procedures for generating random matrices distributed on the space o...
Definition: pm_distCov.F90:72
Warning
The condition all([0 < scale]) must hold for the corresponding input arguments.
These conditions are verified only if the library is built with the preprocessor macro CHECK_ENABLED=1.
Note
Unlike the case for setCovRand, when the input argument scale is missing, the diagonal elements of the output correlation matrix are strictly enforced to 1.


Example usage ⛓

1program example
2
3 use pm_kind, only: SK, IK, LK
4 use pm_io, only: display_type
5 use pm_distUnif, only: getUnifRand
6 use pm_matrixChol, only: setChoLow
7 use pm_distUnifEll, only: getUnifEllRand
8 use pm_matrixClass, only: isMatClass, posdefmat
9 use pm_distCov, only: getCovRand
10
11 implicit none
12
13 integer(IK) :: itry, ndim
14
15 type(display_type) :: disp
16 disp = display_type(file = "main.out.F90")
17
18 block
19 use pm_kind, only: TKG => RKS ! all real kinds are supported.
20 real(TKG), allocatable :: rand(:,:)
21 real(TKG) :: mold
22 real(TKG) :: scale
23 do itry = 1, 5
24 call disp%skip()
25 call disp%show("ndim = getUnifRand(2, 3)")
26 ndim = getUnifRand(2, 3)
27 call disp%show("scale = getUnifRand(1, 10)")
28 scale = getUnifRand(1, 10)
29 call disp%show("rand = getCovRand(mold, ndim)")
30 rand = getCovRand(mold, ndim)
31 call disp%show("rand")
32 call disp%show( rand )
33 call disp%show("isMatClass(rand, posdefmat)")
34 call disp%show( isMatClass(rand, posdefmat) )
35 call disp%show("rand = getCovRand(mold, ndim, scale)")
36 rand = getCovRand(mold, ndim, scale)
37 call disp%show("rand")
38 call disp%show( rand )
39 call disp%show("isMatClass(rand, posdefmat)")
40 call disp%show( isMatClass(rand, posdefmat) )
41 call disp%skip()
42 call disp%skip()
43 call disp%show("rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])")
44 rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
45 call disp%show("rand")
46 call disp%show( rand )
47 call disp%show("isMatClass(rand, posdefmat)")
48 call disp%show( isMatClass(rand, posdefmat) )
49 call disp%skip()
50 end do
51 end block
52
53 block
54 use pm_kind, only: TKG => CKS ! all real kinds are supported.
55 complex(TKG), allocatable :: rand(:,:)
56 complex(TKG) :: mold
57 real(TKG) :: scale
58 do itry = 1, 5
59 call disp%skip()
60 call disp%show("ndim = getUnifRand(2, 3)")
61 ndim = getUnifRand(2, 3)
62 call disp%show("scale = getUnifRand(1, 10)")
63 scale = getUnifRand(1, 10)
64 call disp%show("rand = getCovRand(mold, ndim)")
65 rand = getCovRand(mold, ndim)
66 call disp%show("rand")
67 call disp%show( rand )
68 call disp%show("isMatClass(rand, posdefmat)")
69 call disp%show( isMatClass(rand, posdefmat) )
70 call disp%show("rand = getCovRand(mold, ndim, scale)")
71 rand = getCovRand(mold, ndim, scale)
72 call disp%show("rand")
73 call disp%show( rand )
74 call disp%show("isMatClass(rand, posdefmat)")
75 call disp%show( isMatClass(rand, posdefmat) )
76 call disp%skip()
77 call disp%skip()
78 call disp%show("rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])")
79 rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
80 call disp%show("rand")
81 call disp%show( rand )
82 call disp%show("isMatClass(rand, posdefmat)")
83 call disp%show( isMatClass(rand, posdefmat) )
84 call disp%skip()
85 end do
86 end block
87
88end program example
pm_distUnifEll::getUnifEllRand
Generate and return a (collection) of random vector(s) of size ndim from the ndim-dimensional MultiVa...
Definition: pm_distUnifEll.F90:559
pm_distUnif::getUnifRand
Generate and return a scalar or a contiguous array of rank 1 of length s1 of randomly uniformly distr...
Definition: pm_distUnif.F90:4150
pm_io::show
This is a generic method of the derived type display_type with pass attribute.
Definition: pm_io.F90:11726
pm_io::skip
This is a generic method of the derived type display_type with pass attribute.
Definition: pm_io.F90:11508
pm_matrixChol::setChoLow
[LEGACY code] Return the lower-triangle of the Cholesky factorization of the symmetric positive-def...
Definition: pm_matrixChol.F90:209
pm_matrixClass::isMatClass
Generate and return .true. if and only if the input matrix is of the specified input class.
Definition: pm_matrixClass.F90:2115
pm_distUnifEll
This module contains classes and procedures for computing various statistical quantities related to t...
Definition: pm_distUnifEll.F90:144
pm_distUnif
This module contains classes and procedures for computing various statistical quantities related to t...
Definition: pm_distUnif.F90:274
pm_io
This module contains classes and procedures for input/output (IO) or generic display operations on st...
Definition: pm_io.F90:252
pm_io::disp
type(display_type) disp
This is a scalar module variable an object of type display_type for general display.
Definition: pm_io.F90:11393
pm_kind
This module defines the relevant Fortran kind type-parameters frequently used in the ParaMonte librar...
Definition: pm_kind.F90:268
pm_kind::LK
integer, parameter LK
The default logical kind in the ParaMonte library: kind(.true.) in Fortran, kind(....
Definition: pm_kind.F90:541
pm_kind::CKS
integer, parameter CKS
The single-precision complex kind in Fortran mode. On most platforms, this is a 32-bit real kind.
Definition: pm_kind.F90:570
pm_kind::IK
integer, parameter IK
The default integer kind in the ParaMonte library: int32 in Fortran, c_int32_t in C-Fortran Interoper...
Definition: pm_kind.F90:540
pm_kind::SK
integer, parameter SK
The default character kind in the ParaMonte library: kind("a") in Fortran, c_char in C-Fortran Intero...
Definition: pm_kind.F90:539
pm_kind::RKS
integer, parameter RKS
The single-precision real kind in Fortran mode. On most platforms, this is an 32-bit real kind.
Definition: pm_kind.F90:567
pm_matrixChol
This module contains procedures and generic interfaces for computing the Cholesky factorization of po...
Definition: pm_matrixChol.F90:133
pm_matrixClass
This module contains abstract and concrete derived types that are required for compile-time resolutio...
Definition: pm_matrixClass.F90:82
pm_matrixClass::posdefmat
type(posdefmat_type), parameter posdefmat
This is a scalar parameter object of type hermitian_type that is exclusively used to signify the Herm...
Definition: pm_matrixClass.F90:1030
pm_io::display_type
Generate and return an object of type display_type.
Definition: pm_io.F90:10282

Example Unix compile command via Intel ifort compiler ⛓
1#!/usr/bin/env sh
2rm main.exe
3ifort -fpp -standard-semantics -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
4./main.exe

Example Windows Batch compile command via Intel ifort compiler ⛓
1del main.exe
2set PATH=..\..\..\lib;%PATH%
3ifort /fpp /standard-semantics /O3 /I:..\..\..\include main.F90 ..\..\..\lib\libparamonte*.lib /exe:main.exe
4main.exe

Example Unix / MinGW compile command via GNU gfortran compiler ⛓
1#!/usr/bin/env sh
2rm main.exe
3gfortran -cpp -ffree-line-length-none -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
4./main.exe

Example output ⛓
1
2ndim = getUnifRand(2, 3)
3scale = getUnifRand(1, 10)
4rand = getCovRand(mold, ndim)
5rand
6+1.00000000, -0.678253531
7-0.678253531, +1.00000000
8isMatClass(rand, posdefmat)
9T
10rand = getCovRand(mold, ndim, scale)
11rand
12+64.0000000, -3.33755255
13-3.33755255, +63.9999962
14isMatClass(rand, posdefmat)
15T
16
17
18rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
19rand
20+1.00000000, +1.87044573, -1.68540144, +1.63426292, -0.722899914
21+1.87044573, +3.99999976, -1.86545885, +0.920164824, +0.177879333
22-1.68540144, -1.86545885, +8.99999905, -8.71189404, +3.64769506
23+1.63426292, +0.920164824, -8.71189404, +16.0000000, -2.45268774
24-0.722899914, +0.177879333, +3.64769506, -2.45268774, +25.0000000
25isMatClass(rand, posdefmat)
26T
27
28
29ndim = getUnifRand(2, 3)
30scale = getUnifRand(1, 10)
31rand = getCovRand(mold, ndim)
32rand
33+1.00000000, +0.850945950
34+0.850945950, +1.00000000
35isMatClass(rand, posdefmat)
36T
37rand = getCovRand(mold, ndim, scale)
38rand
39+4.00000000, -1.38679838
40-1.38679838, +4.00000000
41isMatClass(rand, posdefmat)
42T
43
44
45rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
46rand
47+1.00000000, +1.55580175, +1.82904339, -0.210393891, +3.56267190
48+1.55580175, +4.00000000, +4.05974817, +3.07578659, +7.74551964
49+1.82904339, +4.05974817, +9.00000000, +7.66835022, +10.6735783
50-0.210393891, +3.07578659, +7.66835022, +15.9999971, +10.5352306
51+3.56267190, +7.74551964, +10.6735783, +10.5352306, +25.0000000
52isMatClass(rand, posdefmat)
53T
54
55
56ndim = getUnifRand(2, 3)
57scale = getUnifRand(1, 10)
58rand = getCovRand(mold, ndim)
59rand
60+1.00000000, -0.576553762, +0.712023318
61-0.576553762, +1.00000000, -0.718852520
62+0.712023318, -0.718852520, +1.00000000
63isMatClass(rand, posdefmat)
64T
65rand = getCovRand(mold, ndim, scale)
66rand
67+81.0000000, +77.1657639, -65.4065247
68+77.1657639, +80.9999924, -61.6757469
69-65.4065247, -61.6757469, +80.9999924
70isMatClass(rand, posdefmat)
71T
72
73
74rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
75rand
76+1.00000000, -1.13147545, -2.19191217, -2.20564246, +2.74008274
77-1.13147545, +4.00000000, +2.64308381, +2.28928328, -1.62833118
78-2.19191217, +2.64308381, +8.99999809, +10.4355431, -0.602020919
79-2.20564246, +2.28928328, +10.4355431, +16.0000000, +3.75626707
80+2.74008274, -1.62833118, -0.602020919, +3.75626707, +24.9999981
81isMatClass(rand, posdefmat)
82T
83
84
85ndim = getUnifRand(2, 3)
86scale = getUnifRand(1, 10)
87rand = getCovRand(mold, ndim)
88rand
89+1.00000000, -0.797513843, -0.622656584
90-0.797513843, +1.00000000, +0.887649179
91-0.622656584, +0.887649179, +1.00000000
92isMatClass(rand, posdefmat)
93T
94rand = getCovRand(mold, ndim, scale)
95rand
96+1.00000000, -0.754223943, -0.931917250
97-0.754223943, +1.00000000, +0.467446566
98-0.931917250, +0.467446566, +0.999999940
99isMatClass(rand, posdefmat)
100T
101
102
103rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
104rand
105+0.999999881, -0.705764830, +1.10615718, -1.05442274, -1.60689688
106-0.705764830, +4.00000000, -3.93263412, +6.84730196, +2.06657386
107+1.10615718, -3.93263412, +8.99999809, -2.90267181, +7.29608011
108-1.05442274, +6.84730196, -2.90267181, +15.9999990, +9.07913399
109-1.60689688, +2.06657386, +7.29608011, +9.07913399, +25.0000019
110isMatClass(rand, posdefmat)
111T
112
113
114ndim = getUnifRand(2, 3)
115scale = getUnifRand(1, 10)
116rand = getCovRand(mold, ndim)
117rand
118+1.00000000, -0.187521651
119-0.187521651, +1.00000000
120isMatClass(rand, posdefmat)
121T
122rand = getCovRand(mold, ndim, scale)
123rand
124+64.0000000, +49.2762146
125+49.2762146, +63.9999962
126isMatClass(rand, posdefmat)
127T
128
129
130rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
131rand
132+1.00000000, -1.47697520, -0.110004004E-1, +1.99357927, -1.98655176
133-1.47697520, +4.00000048, -3.89132237, -5.92055607, +7.07246113
134-0.110004004E-1, -3.89132237, +8.99999905, +7.61685944, -11.0060549
135+1.99357927, -5.92055607, +7.61685944, +15.9999971, -15.9632530
136-1.98655176, +7.07246113, -11.0060549, -15.9632530, +25.0000000
137isMatClass(rand, posdefmat)
138T
139
140
141ndim = getUnifRand(2, 3)
142scale = getUnifRand(1, 10)
143rand = getCovRand(mold, ndim)
144rand
145(+1.00000000, +0.00000000), (-0.686078370, +0.434828699)
146(-0.686078370, -0.434828699), (+1.00000000, +0.00000000)
147isMatClass(rand, posdefmat)
148T
149rand = getCovRand(mold, ndim, scale)
150rand
151(+36.0000000, +0.00000000), (-20.9644279, +9.64115238)
152(-20.9644279, -9.64115238), (+36.0000038, +0.00000000)
153isMatClass(rand, posdefmat)
154T
155
156
157rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
158rand
159(+1.00000000, +0.00000000), (-0.457986832, +0.00000000), (-1.64626336, +0.00000000), (+2.20828080, +0.00000000), (+1.63638210, +0.00000000)
160(-0.457986832, +0.00000000), (+4.00000048, +0.00000000), (-1.64370024, +0.00000000), (+4.61983347, +0.00000000), (-4.17207336, +0.00000000)
161(-1.64626336, +0.00000000), (-1.64370024, +0.00000000), (+8.99999809, +0.00000000), (-10.5807819, +0.00000000), (+7.99656963, +0.00000000)
162(+2.20828080, +0.00000000), (+4.61983347, +0.00000000), (-10.5807819, +0.00000000), (+16.0000000, +0.00000000), (-6.74015951, +0.00000000)
163(+1.63638210, +0.00000000), (-4.17207336, +0.00000000), (+7.99656963, +0.00000000), (-6.74015951, +0.00000000), (+25.0000000, +0.00000000)
164isMatClass(rand, posdefmat)
165T
166
167
168ndim = getUnifRand(2, 3)
169scale = getUnifRand(1, 10)
170rand = getCovRand(mold, ndim)
171rand
172(+1.00000000, +0.00000000), (-0.587565482, -0.661676705), (-0.222535193, +0.158793837)
173(-0.587565482, +0.661676705), (+1.00000000, +0.00000000), (+0.700510964E-1, -0.586710453)
174(-0.222535193, -0.158793837), (+0.700510964E-1, +0.586710453), (+1.00000000, +0.00000000)
175isMatClass(rand, posdefmat)
176T
177rand = getCovRand(mold, ndim, scale)
178rand
179(+48.9999924, +0.00000000), (-31.0752697, -32.9097061), (+23.7876492, -23.1091728)
180(-31.0752697, +32.9097061), (+48.9999924, +0.00000000), (+0.157827437, +26.0913677)
181(+23.7876492, +23.1091728), (+0.157827437, -26.0913677), (+48.9999924, +0.00000000)
182isMatClass(rand, posdefmat)
183T
184
185
186rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
187rand
188(+1.00000000, +0.00000000), (-1.54050994, +0.00000000), (+0.333717972, +0.00000000), (-1.19415343, +0.00000000), (+0.736712933, +0.00000000)
189(-1.54050994, +0.00000000), (+3.99999976, +0.00000000), (-3.44799280, +0.00000000), (+4.57718182, +0.00000000), (+2.07279730, +0.00000000)
190(+0.333717972, +0.00000000), (-3.44799280, +0.00000000), (+8.99999809, +0.00000000), (-1.40387714, +0.00000000), (+1.37851501, +0.00000000)
191(-1.19415343, +0.00000000), (+4.57718182, +0.00000000), (-1.40387714, +0.00000000), (+16.0000019, +0.00000000), (+13.5879316, +0.00000000)
192(+0.736712933, +0.00000000), (+2.07279730, +0.00000000), (+1.37851501, +0.00000000), (+13.5879316, +0.00000000), (+25.0000000, +0.00000000)
193isMatClass(rand, posdefmat)
194T
195
196
197ndim = getUnifRand(2, 3)
198scale = getUnifRand(1, 10)
199rand = getCovRand(mold, ndim)
200rand
201(+1.00000000, +0.00000000), (-0.517126858, +0.663563609)
202(-0.517126858, -0.663563609), (+1.00000000, +0.00000000)
203isMatClass(rand, posdefmat)
204T
205rand = getCovRand(mold, ndim, scale)
206rand
207(+81.0000000, +0.00000000), (+61.4656792, -26.1785831)
208(+61.4656792, +26.1785831), (+81.0000000, +0.00000000)
209isMatClass(rand, posdefmat)
210T
211
212
213rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
214rand
215(+1.00000000, +0.00000000), (+1.54776490, +0.00000000), (+1.45657814, +0.00000000), (+3.43243718, +0.00000000), (+2.93747044, +0.00000000)
216(+1.54776490, +0.00000000), (+4.00000048, +0.00000000), (+5.57432985, +0.00000000), (+6.66049480, +0.00000000), (+1.95156074, +0.00000000)
217(+1.45657814, +0.00000000), (+5.57432985, +0.00000000), (+9.00000191, +0.00000000), (+7.62362909, +0.00000000), (-1.02295768, +0.00000000)
218(+3.43243718, +0.00000000), (+6.66049480, +0.00000000), (+7.62362909, +0.00000000), (+15.9999981, +0.00000000), (+6.46011639, +0.00000000)
219(+2.93747044, +0.00000000), (+1.95156074, +0.00000000), (-1.02295768, +0.00000000), (+6.46011639, +0.00000000), (+25.0000019, +0.00000000)
220isMatClass(rand, posdefmat)
221T
222
223
224ndim = getUnifRand(2, 3)
225scale = getUnifRand(1, 10)
226rand = getCovRand(mold, ndim)
227rand
228(+1.00000000, +0.00000000), (-0.762964785E-1, +0.261936903), (+0.400371492, +0.284627825)
229(-0.762964785E-1, -0.261936903), (+1.00000000, +0.00000000), (-0.363773525, +0.224467188)
230(+0.400371492, -0.284627825), (-0.363773525, -0.224467188), (+1.00000000, +0.00000000)
231isMatClass(rand, posdefmat)
232T
233rand = getCovRand(mold, ndim, scale)
234rand
235(+16.0000000, +0.00000000), (-0.574790597, -10.3225441), (-7.97072029, +8.25149918)
236(-0.574790597, +10.3225441), (+16.0000038, +0.00000000), (-4.97169638, -9.81996250)
237(-7.97072029, -8.25149918), (-4.97169638, +9.81996250), (+16.0000019, +0.00000000)
238isMatClass(rand, posdefmat)
239T
240
241
242rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
243rand
244(+1.00000000, +0.00000000), (-1.95634520, +0.00000000), (-0.360667944, +0.00000000), (+0.541187823, +0.00000000), (+0.291445613, +0.00000000)
245(-1.95634520, +0.00000000), (+3.99999976, +0.00000000), (-0.454427004E-1, +0.00000000), (+0.185179353, +0.00000000), (-1.27388930, +0.00000000)
246(-0.360667944, +0.00000000), (-0.454427004E-1, +0.00000000), (+8.99999905, +0.00000000), (-6.97992039, +0.00000000), (-1.30858243, +0.00000000)
247(+0.541187823, +0.00000000), (+0.185179353, +0.00000000), (-6.97992039, +0.00000000), (+15.9999990, +0.00000000), (-12.0468855, +0.00000000)
248(+0.291445613, +0.00000000), (-1.27388930, +0.00000000), (-1.30858243, +0.00000000), (-12.0468855, +0.00000000), (+25.0000000, +0.00000000)
249isMatClass(rand, posdefmat)
250T
251
252
253ndim = getUnifRand(2, 3)
254scale = getUnifRand(1, 10)
255rand = getCovRand(mold, ndim)
256rand
257(+1.00000000, +0.00000000), (-0.375887960, +0.998196900E-1), (+0.960442871E-1, -0.499969721)
258(-0.375887960, -0.998196900E-1), (+1.00000000, +0.00000000), (+0.401803136, -0.917571783E-2)
259(+0.960442871E-1, +0.499969721), (+0.401803136, +0.917571783E-2), (+1.00000000, +0.00000000)
260isMatClass(rand, posdefmat)
261T
262rand = getCovRand(mold, ndim, scale)
263rand
264(+36.0000000, +0.00000000), (+7.46848583, +0.224649966), (+19.4333019, +14.4216156)
265(+7.46848583, -0.224649966), (+35.9999962, +0.00000000), (+4.68500662, +11.6969585)
266(+19.4333019, -14.4216156), (+4.68500662, -11.6969585), (+36.0000000, +0.00000000)
267isMatClass(rand, posdefmat)
268T
269
270
271rand = getCovRand(mold = 0._TKG, scale = [(real(itry, TKG), itry = 1, 5)])
272rand
273(+1.00000000, +0.00000000), (-1.31374502, +0.00000000), (-0.987170577, +0.00000000), (-0.516361177, +0.00000000), (+1.40397084, +0.00000000)
274(-1.31374502, +0.00000000), (+4.00000000, +0.00000000), (+2.34914804, +0.00000000), (+3.43394709, +0.00000000), (-5.70366859, +0.00000000)
275(-0.987170577, +0.00000000), (+2.34914804, +0.00000000), (+9.00000000, +0.00000000), (+10.5729828, +0.00000000), (+3.94087410, +0.00000000)
276(-0.516361177, +0.00000000), (+3.43394709, +0.00000000), (+10.5729828, +0.00000000), (+16.0000000, +0.00000000), (+4.61187267, +0.00000000)
277(+1.40397084, +0.00000000), (-5.70366859, +0.00000000), (+3.94087410, +0.00000000), (+4.61187267, +0.00000000), (+25.0000000, +0.00000000)
278isMatClass(rand, posdefmat)
279T
280
281
Test:
test_pm_distCov


Final Remarks ⛓

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For details on the naming conventions, see this page.
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Copyright
Computational Data Science Lab
Author:
Amir Shahmoradi, Monday March 6, 2017, 3:22 pm, Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin.

Definition at line 394 of file pm_distCov.F90.

The documentation for this interface was generated from the following file: