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/dports/math/cmlib/cmlib-3.0_8/src/lindrv/
H A Ddnbsl.f83 INTEGER K,KB,L,LB,LDB,LM,M,MLM,NM1
103 MLM=ML-(LM-1)
104 CALL DAXPY(LM,T,ABE(K+LM,MLM),LDB,B(K+1),1)
138 MLM = ML - (LM - 1)
139 B(K) = B(K) + DDOT(LM,ABE(K+LM,MLM),LDB,B(K+1),1)
H A Dcnbsl.f83 INTEGER K,KB,L,LB,LDB,LM,M,MLM,NM1
103 MLM=ML-(LM-1)
104 CALL CAXPY(LM,T,ABE(K+LM,MLM),LDB,B(K+1),1)
138 MLM = ML - (LM - 1)
139 B(K) = B(K) + CDOTC(LM,ABE(K+LM,MLM),LDB,B(K+1),1)
H A Dsnbsl.f83 INTEGER K,KB,L,LB,LDB,LM,M,MLM,NM1
103 MLM=ML-(LM-1)
104 CALL SAXPY(LM,T,ABE(K+LM,MLM),LDB,B(K+1),1)
138 MLM = ML - (LM - 1)
139 B(K) = B(K) + SDOT(LM,ABE(K+LM,MLM),LDB,B(K+1),1)
/dports/math/slatec/src/
H A Dcnbsl.f82 INTEGER K,KB,L,LB,LDB,LM,M,MLM,NM1
102 MLM=ML-(LM-1)
103 CALL CAXPY(LM,T,ABE(K+LM,MLM),LDB,B(K+1),1)
137 MLM = ML - (LM - 1)
138 B(K) = B(K) + CDOTC(LM,ABE(K+LM,MLM),LDB,B(K+1),1)
H A Dsnbsl.f82 INTEGER K,KB,L,LB,LDB,LM,M,MLM,NM1
102 MLM=ML-(LM-1)
103 CALL SAXPY(LM,T,ABE(K+LM,MLM),LDB,B(K+1),1)
137 MLM = ML - (LM - 1)
138 B(K) = B(K) + SDOT(LM,ABE(K+LM,MLM),LDB,B(K+1),1)
H A Ddnbsl.f82 INTEGER K,KB,L,LB,LDB,LM,M,MLM,NM1
102 MLM=ML-(LM-1)
103 CALL DAXPY(LM,T,ABE(K+LM,MLM),LDB,B(K+1),1)
137 MLM = ML - (LM - 1)
138 B(K) = B(K) + DDOT(LM,ABE(K+LM,MLM),LDB,B(K+1),1)
/dports/net-mgmt/librenms/librenms-21.5.1/tests/snmpsim/
H A Dfs-switch_5800.snmprec684 1.3.6.1.2.1.17.7.1.4.3.1.1.797|4|INT-Link-VXO-MLM
685 1.3.6.1.2.1.17.7.1.4.3.1.1.800|4|Link-VXO-MLM
/dports/math/R-cran-VGAM/VGAM/man/
H A DgaitzetaUC.Rd24 and the multinomial logit model (MLM) respectively.
26 GAAIIT--Zeta(shape.p)--Zeta(shape.a)--MLM--Zeta(shape.i)--MLM,
127 %(ii) GAIT--Zeta(\code{shape.p})--MLM(\code{alt.mlm},
128 %\code{pobs.mlm})--MLM(\code{inf.mlm}, \code{pstr.mlm}).
H A DgaitlogUC.Rd24 and the multinomial logit model (MLM) respectively.
26 GAAIIT--Log(shape.p)--Log(shape.a)--MLM--Log(shape.i)--MLM,
128 %(ii) GAIT--Log(\code{shape.p})--MLM(\code{alt.mlm},
129 %\code{pobs.mlm})--MLM(\code{inf.mlm}, \code{pstr.mlm}).
H A Dgaitpoisson.Rd173 % logit model (MLM) probabilities of observing those
180 % MLM structural probabilities are modelled---see
240 Constrain the MLM probabilities to be equal?
263 \code{"pstr.mlm"} for a GAT--MLM model.
380 By default, all the MLM probabilities are
386 To model all the MLM probabilities with covariates
391 For the MLM probabilities,
412 GAIT--Pois--Pois--MLM--Pois-MLM combo model
527 A nonparametric special case submodel is the GAIT--Pois--MLM--MLM,
538 two sources: the parent distribution and a MLM.
[all …]
H A DgaitpoisUC.Rd24 and the multinomial logit model (MLM) respectively.
26 GAAIIT--Pois(lambda.p)--Pois(lambda.a)--MLM--Pois(lambda.i)--MLM,
115 Similar to the above, but for the nonparametric (MLM) variant.
207 The MLM is a loose coupling that effectively separates
256 (ii) GAIT--Pois(\code{lambda.p})--MLM(\code{alt.mlm},
257 \code{pobs.mlm})--MLM(\code{inf.mlm}, \code{pstr.mlm}).
398 % The MLM variant is called nonparametric while the
401 % removed from the main analysis because the MLM provides a
H A DgaitbinomUC.Rd24 and the multinomial logit model (MLM) respectively.
26 GAAIIT--Binom(size.p, prob.p)--Binom(size.a, prob.a)--MLM--Binom(size.i,
27 prob.i)--MLM,
H A DgaitnbinomUC.Rd24 and the multinomial logit model (MLM) respectively.
26 GAAIIT--NB(size.p, munb.p)--NB(size.a, munb.a)--MLM--NB(size.i,
27 munb.i)--MLM,
/dports/biology/molden/molden5.8/plush/
H A DMLM1 mol="MLM" Charge="0"
/dports/games/stonesoup/crawl-0.27.1/crawl-ref/source/dat/des/serial/
H A Dcolumn_ruins.des702 MLM
704 MLM
863 MLM
878 MLM
884 MLM
/dports/net-p2p/jackett/Jackett/Definitions/
H A Dthevault.yml29 - {id: 114, cat: Other, desc: "Network Marketing (MLM)"}
/dports/games/stonesoup/crawl-0.27.1/crawl-ref/source/dat/des/variable/
H A Dd_encompass.des250 v%''c.NO~~~~~..+'''%bnlll"_""""""lbbbbck'cc..~~MLM~..+'''v
251 v['3c..~~~~~ML.c'5'}Gnl^H""""""U"lllnb%'''+..MLM~~~..c''%v
252 v%''c..~~~MLM..+'''%bnlll"U""""""u^lnI]'7'c.LM~~~~~..c1'{v
253 v'''+..~MLM~~..cc'icbbbbl""""""_"lllnb%'''+..~~~~~ON.c''%v
/dports/mail/p5-Mail-OpenDKIM/Mail-OpenDKIM-4204/
H A DREADME38 id => 'MLM',
/dports/lang/fpc-source/fpc-3.2.2/packages/amunits/examples/otherlibs/
H A Dsymbol.green1 …MLM^ZZ]IZIML<L<L00M�r''rA0):0<?0000:0-:0-):-):-))#))#)))))))Ufrfffrrrf{�{Zc��ff��…
/dports/science/hepmc3/HepMC3-3.2.4/examples/LHEFExample/
H A DLHEF_example_cmp.lhe632 # After showering an MLM-type merging should be applied as well. *
777 # After showering an MLM-type merging should be applied as well. *
922 # After showering an MLM-type merging should be applied as well. *
1067 # After showering an MLM-type merging should be applied as well. *
/dports/mail/ecartis/ecartis-1.0.0/documentation/
H A Decartis.tex75 for them; hence the term mailing list manager, or MLM for short. Many people
120 MLM. Soon thereafter, others created similar packages for other systems, such
139 MLM called Lyris, which is targeted specifically at business users) at
193 for ListSTAR, a defunct MLM for Apple computers. Despite the obvious
775 control of an MLM). This method is referred to as using `cookies.'
/dports/textproc/R-cran-stringi/stringi/src/icu55/common/
H A Ducnvisci.c94 MLM = 0x49, enumerator
149 { MALAYALAM, MLM_MASK, MLM }
/dports/www/firefox-legacy/firefox-52.8.0esr/intl/icu/source/common/
H A Ducnvisci.c96 MLM = 0x49, enumerator
151 { MALAYALAM, MLM_MASK, MLM }
/dports/databases/mongodb36/mongodb-src-r3.6.23/src/third_party/icu4c-57.1/source/common/
H A Ducnvisci.c94 MLM = 0x49, enumerator
149 { MALAYALAM, MLM_MASK, MLM }
/dports/mail/junkfilter/junkfilter/
H A Djf-bodychk1 …commendation)|(sujet|subject) $JFBRM|(this is not|dies ist kein)(a )?(spam|MLM)|(to|for) opt[ -]?o…

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