/dports/math/R-cran-VGAM/VGAM/man/ |
H A D | zanegbinomial.Rd | 7 Fits a zero-altered negative binomial distribution based on 8 a conditional model involving a binomial distribution and a 9 positive-negative binomial distribution. 38 \eqn{\mu_{nb}}{munb} of an ordinary negative binomial distribution. 137 or \eqn{Y} has a positive-negative binomial distribution with 140 negative binomial distribution differs from the zero-inflated negative 141 binomial distribution in that the former has zeros coming from one 142 source, whereas the latter has zeros coming from the negative binomial 143 distribution too. The zero-inflated negative binomial distribution 145 call the zero-altered negative binomial a \emph{hurdle} model. [all …]
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/dports/math/R-cran-statmod/statmod/man/ |
H A D | sage.test.Rd | 8 The counts in each group as a proportion of the whole are assumed to follow a binomial distribution. 30 An exact two-sided binomial test is computed for each tag. 32 …counts are in the same proportions as the library sizes, i.e., that the binomial probability for t… 38 When the counts are reasonably large, the binomial test, Fisher's test and Pearson's chisquare all … 39 When the counts are smaller, the binomial test is usually to be preferred in this context. 72 \code{\link{binom.test}} in the stats package performs univariate binomial tests.
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/dports/math/maxima/maxima-5.43.2/share/sym/ |
H A D | kak.lisp | 97 (let* ((binnk (binomial n k)) 121 (binomial (- n i) 164 (let* ((binnk (binomial n k)) 180 ($piej l infkl 0 (binomial (- n l) (- k l)) n ) 234 (let ((nxcoe ($mult_sym (car poule) (binomial pui ote))) 254 (let* ((binnk (binomial n k))
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/dports/math/reduce/Reduce-svn5758-src/doc/manual2/ |
H A D | zeilberg.tex | 22 products of powers, factorials, $\Gamma$ function terms, binomial 56 gosper(binomial(k,n),k); 58 (k + 1)*binomial(k,n) 86 extended_gosper(binomial(k/2,n),k); 89 (k + 2)*binomial(---,n) + (k + 1)*binomial(-------,n) 125 sumrecursion(binomial(n,k),k,n); 231 expressions given in factorial-$\Gamma$-binomial-Pochhammer notation 245 factorial-$\Gamma$-binomial-Poch\-hammer notation are converted into 269 sumtohyper(binomial(n,k)^3,k); 292 $\Gamma$ function terms, binomial coefficients, and Pochhammer symbols [all …]
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/dports/math/R-cran-gss/gss/ |
H A D | INDEX | 127 mkdata.binomial Making pseudo data for logistic regression 128 dev.resid.binomial Deviance residuals for logistic regression 129 dev.null.binomial Null model deviance for logistic regression 130 cv.binomial CV score for logistic regression 131 y0.binomial Preparing for KL projection of logistic fit 132 proj0.binomial Making pseudo data for projection of logistic fit 133 kl.binomial Computing KL distance between logistic fits 134 cfit.binomial Computing constant logistic fit 163 mkdata.nbinomial Making pseudo data for negative binomial regression 166 cv.nbinomial CV score for negative binomial regression [all …]
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/dports/databases/percona57-pam-for-mysql/boost_1_59_0/libs/math/doc/distributions/ |
H A D | binomial.qbk | 3 ``#include <boost/math/distributions/binomial.hpp>`` 11 typedef binomial_distribution<> binomial; 64 binomial distribution assumes that p is fixed for all trials. 68 whereas for the negative binomial, 71 The PDF for the binomial distribution is given by: 302 `pdf(binomial(n, p), k)`]] 307 `cdf(binomial(n, p), k)`]] 312 `cdf(complement(binomial(n, p), k))`]] 319 `quantile(binomial(n, p), P)`]] 326 `quantile(complement(binomial(n, p), P))`]] [all …]
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/dports/databases/percona57-server/boost_1_59_0/libs/math/doc/distributions/ |
H A D | binomial.qbk | 3 ``#include <boost/math/distributions/binomial.hpp>`` 11 typedef binomial_distribution<> binomial; 64 binomial distribution assumes that p is fixed for all trials. 68 whereas for the negative binomial, 71 The PDF for the binomial distribution is given by: 302 `pdf(binomial(n, p), k)`]] 307 `cdf(binomial(n, p), k)`]] 312 `cdf(complement(binomial(n, p), k))`]] 319 `quantile(binomial(n, p), P)`]] 326 `quantile(complement(binomial(n, p), P))`]] [all …]
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/dports/databases/xtrabackup/boost_1_59_0/libs/math/doc/distributions/ |
H A D | binomial.qbk | 3 ``#include <boost/math/distributions/binomial.hpp>`` 11 typedef binomial_distribution<> binomial; 64 binomial distribution assumes that p is fixed for all trials. 68 whereas for the negative binomial, 71 The PDF for the binomial distribution is given by: 302 `pdf(binomial(n, p), k)`]] 307 `cdf(binomial(n, p), k)`]] 312 `cdf(complement(binomial(n, p), k))`]] 319 `quantile(binomial(n, p), P)`]] 326 `quantile(complement(binomial(n, p), P))`]] [all …]
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/dports/databases/percona57-client/boost_1_59_0/libs/math/doc/distributions/ |
H A D | binomial.qbk | 3 ``#include <boost/math/distributions/binomial.hpp>`` 11 typedef binomial_distribution<> binomial; 64 binomial distribution assumes that p is fixed for all trials. 68 whereas for the negative binomial, 71 The PDF for the binomial distribution is given by: 302 `pdf(binomial(n, p), k)`]] 307 `cdf(binomial(n, p), k)`]] 312 `cdf(complement(binomial(n, p), k))`]] 319 `quantile(binomial(n, p), P)`]] 326 `quantile(complement(binomial(n, p), P))`]] [all …]
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/dports/databases/mysqlwsrep57-server/boost_1_59_0/libs/math/doc/distributions/ |
H A D | binomial.qbk | 3 ``#include <boost/math/distributions/binomial.hpp>`` 11 typedef binomial_distribution<> binomial; 64 binomial distribution assumes that p is fixed for all trials. 68 whereas for the negative binomial, 71 The PDF for the binomial distribution is given by: 302 `pdf(binomial(n, p), k)`]] 307 `cdf(binomial(n, p), k)`]] 312 `cdf(complement(binomial(n, p), k))`]] 319 `quantile(binomial(n, p), P)`]] 326 `quantile(complement(binomial(n, p), P))`]] [all …]
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/dports/math/py-Diofant/Diofant-0.13.0/diofant/stats/ |
H A D | frv_types.py | 19 from ..functions import KroneckerDelta, binomial 239 binomial(n, k) * p**k * (1 - p)**(n - k) for k in range(n + 1)} 270 Rational(binomial(m, k) * binomial(N - m, n - k), 271 binomial(N, n))
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/dports/devel/R-cran-ModelMetrics/ModelMetrics/man/ |
H A D | mauc.Rd | 18 setosa <- glm(I(Species == 'setosa') ~ Sepal.Length, data = iris, family = 'binomial') 19 versicolor <- glm(I(Species == 'versicolor') ~ Sepal.Length, data = iris, family = 'binomial') 20 virginica <- glm(I(Species == 'virginica') ~ Sepal.Length, data = iris, family = 'binomial')
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/dports/math/py-sympy/sympy-1.9/sympy/simplify/tests/ |
H A D | test_gammasimp.py | 2 Rational, gammasimp, factorial, gamma, binomial, pi, S, 32 assert gammasimp(binomial(n, k)) == \ 66 assert gammasimp(rf(x + n, k)*binomial(n, k)).simplify() == Piecewise( 84 assert gammasimp(binomial(n + 2, k + S.Half)) == gamma(n + 3)/ \ 86 assert gammasimp(binomial(n + 2, k + 2.0)) == \ 90 assert gammasimp(binomial(0, x)) == sin(pi*x)/(pi*x)
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/dports/science/R-cran-epicalc/epicalc/man/ |
H A D | poisgof.rd | 4 \description{Poisson and negative binomial regression are used for modeling count data. This comman… 9 \item{model}{A Poisson or negative binomial model} 12 To test the significance of overdispersion of the errors of a Poisson or negative binomial model, t…
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/dports/finance/R-cran-AER/AER/man/ |
H A D | MurderRates.Rd | 53 fm_logit <- glm(model, data = MurderRates, family = binomial) 56 fm_logit2 <- glm(model, data = MurderRates, family = binomial, 60 fm_probit <- glm(model, data = MurderRates, family = binomial(link = "probit")) 63 fm_probit2 <- glm(model, data = MurderRates , family = binomial(link = "probit"),
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/dports/lang/v8/v8-9.6.180.12/tools/clang/translation_unit/test_files/ |
H A D | binomial.h | 8 int binomial(int n, int k) { in binomial() function 9 return k > 0 ? binomial(n - 1, k - 1) * n / k : 1; in binomial()
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/dports/www/qt5-webengine/qtwebengine-everywhere-src-5.15.2/src/3rdparty/chromium/tools/clang/translation_unit/test_files/ |
H A D | binomial.h | 8 int binomial(int n, int k) { in binomial() function 9 return k > 0 ? binomial(n - 1, k - 1) * n / k : 1; in binomial()
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/dports/www/chromium-legacy/chromium-88.0.4324.182/tools/clang/translation_unit/test_files/ |
H A D | binomial.h | 8 int binomial(int n, int k) { in binomial() function 9 return k > 0 ? binomial(n - 1, k - 1) * n / k : 1; in binomial()
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/dports/lang/chibi-scheme/chibi-scheme-0.10/tests/snow/repo3/pingala/ |
H A D | binomial.scm | 1 (define-library (pingala binomial) 2 (export binomial)
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/dports/math/py-Diofant/Diofant-0.13.0/diofant/functions/combinatorial/ |
H A D | numbers.py | 26 from .factorials import binomial, factorial 255 a = int(binomial(n + 3, n - 6)) 265 return s / binomial(n + 3, n) 865 return binomial(2*n, n)/(n + 1) 1256 from .factorials import binomial 1266 return binomial(n + k - 1, k) 1267 return binomial(n, k) 1300 return binomial(n, 2) 1302 return (3*n - 1)*binomial(n, 3)/4 1304 return binomial(n, 2)*binomial(n, 4) [all …]
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/dports/math/py-mpmath/mpmath-1.2.1/mpmath/tests/ |
H A D | test_gammazeta.py | 222 assert binomial(0,0) == 1 223 assert binomial(1,0) == 1 224 assert binomial(0,-1) == 0 225 assert binomial(3,2) == 3 226 assert binomial(5,2) == 10 227 assert binomial(5,3) == 10 228 assert binomial(5,5) == 1 229 assert binomial(-1,0) == 1 230 assert binomial(-2,-4) == 3 232 assert binomial(1100,1) == 1100 [all …]
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/dports/math/octave-forge-statistics/statistics-1.4.3/inst/ |
H A D | random.m | 45 ## @itemx "binomial" 46 ## @itemx "binomial distribution" 76 ## @itemx "negative binomial" 77 ## @itemx "negative binomial distribution" 124 case {"bino", "binomial", "binomial distribution"} 146 case {"nbin", "negative binomial", "negative binomial distribution"}
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/dports/finance/quantlib/QuantLib-1.20/ql/experimental/credit/ |
H A D | lossdistribution.cpp | 30 BinomialDistribution binomial (p[0], p.size()); in binomialProbabilityOfNEvents() local 31 return binomial(n); in binomialProbabilityOfNEvents() 37 CumulativeBinomialDistribution binomial(p[0], p.size()); in binomialProbabilityOfAtLeastNEvents() local 38 return 1.0 - binomial(n-1); in binomialProbabilityOfAtLeastNEvents() 153 BinomialDistribution binomial (probability, n); in operator ()() local 156 probability_[i] = binomial(i); in operator ()()
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/dports/math/dune-localfunctions/dune-localfunctions-f6628171b2773065ab43f97a77f47cd8c4283d8f/dune/localfunctions/brezzidouglasfortinmarini/cube/ |
H A D | localinterpolation.hh | 45 static constexpr unsigned int interiorDofs = dim*binomial(dim+order-2, order-2); 46 static constexpr unsigned int faceDofs = binomial(dim+order-2, order-1); 85 assert( i < binomial(d+kMax, kMax)); in unrank() 92 for(;k <= kMax && b <= i; ++k, b = binomial(d+k-1, k)) in unrank() 99 for(; m <= k && c <= i; ++m, c = binomial(d-p+m-2, m)) in unrank()
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/dports/math/dune-common/dune-common-df65b1282ea89ad40d2cb6565983f7e633ccce31/dune/common/ |
H A D | math.hh | 128 constexpr inline static T binomial (const T& n, const T& k) noexcept in binomial() function 136 return binomial(n, n-k); in binomial() 146 …constexpr inline static auto binomial (std::integral_constant<T, n>, std::integral_constant<T, k>)… in binomial() function 148 return std::integral_constant<T, binomial(n, k)>{}; in binomial() 152 …constexpr inline static auto binomial (std::integral_constant<T, n>, std::integral_constant<T, n>)… in binomial() function
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