/dports/math/cado-nfs/cado-nfs-f4284e2391121b2bfb97bc4880b6273c7250dc2f/polyselect/ |
H A D | sopt.c | 109 double lognorm, alpha, alpha_proj, exp_E; in main() local 114 lognorm = L2_lognorm (poly->pols[ALG_SIDE], poly->skew); in main() 117 exp_E = lognorm in main() 123 ave_raw_lognorm += lognorm; in main() 124 min_raw_lognorm = (lognorm < min_raw_lognorm) ? lognorm : min_raw_lognorm; in main() 125 max_raw_lognorm = (lognorm > max_raw_lognorm) ? lognorm : max_raw_lognorm; in main() 139 lognorm = L2_lognorm (poly->pols[ALG_SIDE], poly->skew); in main() 142 exp_E = lognorm in main() 149 ave_sopt_lognorm += lognorm; in main() 150 min_sopt_lognorm = (lognorm < min_sopt_lognorm) ? lognorm : min_sopt_lognorm; in main() [all …]
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H A D | ropt_str.c | 41 double lognorm, exp_E = DBL_MAX, min_exp_E = DBL_MAX; in rotate_bounds_V_mpz() local 72 exp_E = lognorm + expected_rotation_gain (F, G); in rotate_bounds_V_mpz() 80 if (lognorm > bound->bound_lognorm) break; in rotate_bounds_V_mpz() 95 exp_E = lognorm + expected_rotation_gain (F, G); in rotate_bounds_V_mpz() 103 if (lognorm > bound->bound_lognorm) break; in rotate_bounds_V_mpz() 145 exp_E = lognorm + expected_rotation_gain (F, G); in rotate_bounds_U_lu() 153 if (lognorm > bound->bound_lognorm) break; in rotate_bounds_U_lu() 168 exp_E = lognorm + expected_rotation_gain (F, G); in rotate_bounds_U_lu() 176 if (lognorm > bound->bound_lognorm) break; in rotate_bounds_U_lu() 215 if (lognorm > bound->bound_lognorm) in rotate_bounds_W_lu() [all …]
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H A D | rotate_all.c | 282 double lognorm, alpha, E0, E, best_E; in rotate_bounds() local 301 lognorm = L2_skew_lognorm (f, SKEWNESS_DEFAULT_PREC); in rotate_bounds() 303 E = lognorm + alpha; in rotate_bounds() 320 lognorm = L2_skew_lognorm (f, SKEWNESS_DEFAULT_PREC); in rotate_bounds() 322 E = lognorm + alpha; in rotate_bounds() 365 double *A, alpha, lognorm, best_alpha = DBL_MAX, best_lognorm = DBL_MAX; in rotate() local 486 lognorm = L2_skew_lognorm (f, SKEWNESS_DEFAULT_PREC); in rotate() 488 if (lognorm + alpha < best_lognorm + best_alpha) { in rotate() 489 best_lognorm = lognorm; in rotate() 497 double newE = lognorm + alpha; in rotate()
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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/snowpac/include/ |
H A D | NoiseDetection.hpp | 29 std::vector<double> lognorm; member in NoiseDetection 55 lognorm.resize( nb_surrogate_models); in initialize_noise_detection() 93 lognorm[ i ] = norm( (*surrogate_models)[i].hessian() ) / ((*delta)*(*delta)); in detect_noise() 94 if ( fabs(lognorm [ i ]) < 1e-16 ) { in detect_noise() 120 norms_of_hessians[i].push_back( lognorm[i] ); in detect_noise() 121 lognorm[i] = log( lognorm[i] ); in detect_noise() 122 sum_norms_tr_radii[i] += lognorm[i] * logdelta; in detect_noise() 123 sum_norms[i] += lognorm[i]; in detect_noise()
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/dports/math/R-cran-gss/gss/man/ |
H A D | family.Rd | 58 \alias{mkdata.lognorm} 59 \alias{dev.resid.lognorm} 60 \alias{dev0.resid.lognorm} 61 \alias{dev.null.lognorm} 62 \alias{cv.lognorm} 63 \alias{y0.lognorm} 64 \alias{proj0.lognorm} 65 \alias{kl.lognorm} 66 \alias{cfit.lognorm} 150 y0.lognorm(y, eta0, nu) [all …]
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/dports/devel/liblognorm/liblognorm-2.0.6/src/ |
H A D | Makefile.am | 29 lognorm.c \ 55 lognorm.h \ 70 include_HEADERS = liblognorm.h samp.h lognorm.h pdag.h annot.h enc.h parser.h lognorm-features.h
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H A D | Makefile.in | 107 CONFIG_CLEAN_FILES = lognorm-features.h 144 liblognorm_la-samp.lo liblognorm_la-lognorm.lo \ 232 $(srcdir)/lognorm-features.h.in $(top_srcdir)/depcomp 387 liblognorm_la_SOURCES = liblognorm.c pdag.c annot.c samp.c lognorm.c \ 398 EXTRA_DIST = internal.h liblognorm.h lognorm.h pdag.h annot.h samp.h \ 401 include_HEADERS = liblognorm.h samp.h lognorm.h pdag.h annot.h enc.h parser.h lognorm-features.h 435 lognorm-features.h: $(top_builddir)/config.status $(srcdir)/lognorm-features.h.in 553 @AMDEP_TRUE@@am__include@ @am__quote@./$(DEPDIR)/liblognorm_la-lognorm.Plo@am__quote@ 613 liblognorm_la-lognorm.lo: lognorm.c 614 …orm_la-lognorm.lo -MD -MP -MF $(DEPDIR)/liblognorm_la-lognorm.Tpo -c -o liblognorm_la-lognorm.lo `… [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/sandbox/distributions/examples/ |
H A D | ex_fitfr.py | 27 x = stats.lognorm.rvs(2, loc=0, scale=2, size=200) 28 print(stats.lognorm.fit_fr(x, frozen=[np.nan, 0., np.nan]))
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H A D | ex_extras.py | 91 print(stats.lognorm.cdf(1,1)) 93 print(stats.lognorm.stats(1))
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/dports/devel/liblognorm/liblognorm-2.0.6/doc/ |
H A D | contacts.rst | 8 mailing list lognorm@lists.adiscon.com. 10 To subscribe: http://lists.adiscon.net/mailman/listinfo/lognorm
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/dports/math/R-cran-gss/gss/R/ |
H A D | project.gssanova.R | 38 lognorm=y0.lognorm(y,eta,nu), 49 lognorm=cfit.lognorm(y,wt,offset,nu), 60 lognorm=kl.lognorm(eta,cfit,wt,nu,y0), 173 lognorm=kl.lognorm(eta1,cfit,wt,nu,y0), 197 lognorm=proj0.lognorm(y0,eta,wt,offset,nu), 216 lognorm=proj0.lognorm(y0,eta.new,wt,offset,nu), 251 lognorm=proj0.lognorm(y0,eta,wt,offset,nu), 310 lognorm=proj0.lognorm(y0,eta,wt,offset,nu), 339 lognorm=proj0.lognorm(y0,eta,wt,offset,nu),
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H A D | fitted.R | 46 lognorm=mkdata.lognorm(y,object$eta,wt,offset,list(object$nu,FALSE)), 58 lognorm=dev.resid.lognorm(y,object$eta,wt,object$nu),
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/dports/finance/py-quantecon/quantecon-0.5.2/quantecon/tests/ |
H A D | test_lae.py | 9 from scipy.stats import lognorm 17 phi = lognorm(a_sigma)
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/dports/math/cado-nfs/cado-nfs-f4284e2391121b2bfb97bc4880b6273c7250dc2f/sieve/ |
H A D | las-duplicate.cpp | 165 subtract_fb_log(const unsigned char lognorm, in subtract_fb_log() argument 172 unsigned char new_lognorm = lognorm; in subtract_fb_log() 266 const uint8_t lognorm = L.lognorm(i,j); in sq_finds_relation() local 268 remaining_lognorm[side] = subtract_fb_log(lognorm, L.scale, in sq_finds_relation()
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/dports/math/cado-nfs/cado-nfs-f4284e2391121b2bfb97bc4880b6273c7250dc2f/scripts/ |
H A D | check_dup.py | 51 lognorm = tuple(ij_lognorm[2:4]) 53 if lognorm != new_lognorm: 55 % (new_lognorm + lognorm))
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/dports/devel/liblognorm/liblognorm-2.0.6/ |
H A D | configure.ac | 8 AC_CONFIG_SRCDIR([src/lognorm.c]) 165 [AS_HELP_STRING([--enable-tools],[lognorm toolset enabled @<:@default=yes@:>@])], 176 lognorm.pc \ 180 src/lognorm-features.h \
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H A D | Makefile.am | 9 pkgconfig_DATA = lognorm.pc
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/dports/math/R-cran-Zelig/Zelig/man/ |
H A D | Zelig-lognorm-class.Rd | 2 % Please edit documentation in R/model-lognorm.R 4 \name{Zelig-lognorm-class} 5 \alias{Zelig-lognorm-class} 89 z.out <- zelig(Surv(duration, ciep12) ~ fract + numst2, model ="lognorm", data = coalition)
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/dports/math/R-cran-gss/gss/ |
H A D | INDEX | 190 mkdata.lognorm Making pseudo data for log normal regression 191 dev.resid.lognorm Deviance residuals for log normal regression 192 dev0.resid.lognorm Pseudo deviance residuals for log normal regression 193 dev.null.lognorm Null model deviance for log normal regression 194 cv.lognorm CV score for log normal regression 195 y0.lognorm Preparing for KL projection of log normal fit 196 proj0.lognorm Making pseudo data for projection of log normal fit 197 kl.lognorm Computing KL distance between log normal fits 198 cfit.lognorm Computing constant log normal fit
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/dports/science/py-scipy/scipy-1.7.1/doc/source/tutorial/stats/ |
H A D | continuous_lognorm.rst | 2 .. _continuous-lognorm: 35 Implementation: `scipy.stats.lognorm`
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/dports/math/cado-nfs/cado-nfs-f4284e2391121b2bfb97bc4880b6273c7250dc2f/utils/ |
H A D | cado_poly.c | 378 cado_poly_fprintf_info (FILE *fp, double lognorm, double exp_E, double alpha, in cado_poly_fprintf_info() argument 387 lognorm, (exp_E == 0) ? "E" : "exp_E", in cado_poly_fprintf_info() 388 (exp_E == 0) ? lognorm + alpha : exp_E, alpha, alpha_proj, in cado_poly_fprintf_info()
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/dports/math/cado-nfs/cado-nfs-f4284e2391121b2bfb97bc4880b6273c7250dc2f/tests/sieve/ |
H A D | c120.poly | 12 # lognorm 36.62
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/dports/math/cado-nfs/cado-nfs-f4284e2391121b2bfb97bc4880b6273c7250dc2f/tests/misc/ |
H A D | c60.poly | 11 # lognorm 20.1
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/dports/math/cado-nfs/cado-nfs-f4284e2391121b2bfb97bc4880b6273c7250dc2f/parameters/polynomials/ |
H A D | rsa220.poly | 13 # lognorm: 62.58, alpha: -9.12 (proj: -3.05), E: 53.47, nr: 6
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H A D | c150.poly | 12 # lognorm 45.32
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