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/dports/biology/ncbi-cxx-toolkit/ncbi_cxx--25_2_0/src/algo/gnomon/
H A Dgnomon.asn19 start Markov-chain-array ,
20 stop Markov-chain-array ,
21 donor Markov-chain-array ,
22 acceptor Markov-chain-array ,
23 coding-region SEQUENCE OF Markov-chain-params , -- three elements (per phase)
24 non-coding-region Markov-chain-params } }
54 Markov-chain-params ::= SEQUENCE {
58 prev-order Markov-chain-params,
61 Markov-chain-array ::= SEQUENCE {
64 matrix SEQUENCE OF Markov-chain-params -- in-exon+in-intron elements
/dports/security/john/john-1.9.0-jumbo-1/doc/
H A DMARKOV20 [Markov:MODE]. The Markov mode name is not case sensitive.
22 [Markov:Default] is used.
24 * LEVEL is the "Markov level".
30 [Markov::MODE] section (the MkvLvl = xxx item)
34 read from config variables in the [Markov:mode] section, or [Markov:Default]
127 [Markov:MODE].
141 or if the Markov level specified on the command line is 0.
154 or if the Markov level specified on the command line was 0.
155 (In other words, when the max. Markov level is read from the Markov mode
156 section, the min. Markov level will be read from the Markov mode section as
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/dports/math/4ti2/4ti2-Release_1_6_9/src/groebner/
H A DMarkov.cpp39 Markov::Markov(Generation* _gen) in Markov() function in Markov
45 Markov::~Markov() in ~Markov()
50 Markov::compute( in compute()
83 Markov::compute( in compute()
119 Markov::algorithm( in algorithm()
189 Markov::fast_algorithm( in fast_algorithm()
H A DMarkov.h36 class Markov
39 Markov(Generation* gen = 0);
40 virtual ~Markov();
/dports/science/agrum/aGrUM-29e540d8169268e8fe5d5c69bc4b2b1290f12320/wrappers/pyAgrum/doc/sphinx/
H A DmarkovNetwork.rst1 Markov Network
6 :alt: a Markov network as an unoriented graph and as a factor graph
8 A Markov network is a undirected probabilistic graphical model. It represents a joint distribution …
10 A Markov network uses a undirected graph to represent conditional independence in the joint distrib…
21 * `Tutorial on Markov Network <https://lip6.fr/Pierre-Henri.Wuillemin/aGrUM/docs/current/notebooks/…
H A DMNInference.rst3 …n from a Markov network and some evidence. aGrUM/pyAgrum mainly focus and the computation of (join…
4 … task (NP-complete). For now, aGrUM/pyAgrum implements only one exact inference for Markov Network.
/dports/math/openturns/openturns-1.18/python/src/
H A DDiscreteMarkovChain_doc.i.in2 "Discrete Markov chain process.
7 Probability distribution of the Markov chain origin, i.e. state of the process at :math:`t_0`.
22 A discrete Markov chain is a process :math:`X: \Omega \times \cD \rightarrow E`, where :math:`\cD=\…
47 Create a Markov chain:
75 The probability distribution of the origin of the Markov chain."
93 The probability distribution of the origin of the Markov chain."
97 "Compute the stationary distribution of the Markov chain.
102 The stationary probability distribution of the Markov chain:
108 Compute the stationary distribution of a Markov chain:
/dports/math/octave-forge-queueing/queueing/
H A DDESCRIPTION6 Title: Octave package for Queueing Networks and Markov chains analysis
8 networks and Markov chains analysis. This package can be used to
13 performance measures for Markov chains can be computed, such as state
15 sojourn times and so forth. Discrete- and continuous-time Markov
H A DINDEX1 queueing >> Queueing Networks and Markov chains
2 Discrete-time Markov chains
11 Continuous-time Markov chains
/dports/math/octave-forge-queueing/queueing/doc/
H A Dmarkovchains.texi24 @node Markov Chains
25 @chapter Markov Chains
28 * Discrete-Time Markov Chains::
29 * Continuous-Time Markov Chains::
32 @node Discrete-Time Markov Chains
33 @section Discrete-Time Markov Chains
85 @cindex Markov chain, discrete time
87 @cindex discrete time Markov chain
107 @cindex discrete time Markov chain
109 @cindex irreducible Markov chain
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/dports/math/R-cran-mcmc/mcmc/man/
H A Dinitseq.Rd5 Variance of sample mean of functional of reversible Markov chain
13 Markov chain.}
25 assuming the input time series is a scalar-valued functional of a reversible Markov
31 and convex. It also estimates the variance in the Markov chain central
36 scalar functionals of a reversible Markov chain. Thus these initial sequence
60 the asymptotic variance in the Markov chain CLT. Divide by \code{length(x)}
63 the asymptotic variance in the Markov chain CLT. Divide by \code{length(x)}
66 the asymptotic variance in the Markov chain CLT. Divide by \code{length(x)}
76 Practical Markov Chain Monte Carlo.
H A Dmorph.metrop.Rd7 Markov chain Monte Carlo for continuous random vector using a
28 \code{morph.metrop} implements morphometric methods for Markov
33 run for the induced density. The Markov chain is transformed back to
35 density, instead of the original density, can result in a Markov chain
46 of \eqn{f^{-1}}. Because \eqn{f} is a diffeomorphism, a Markov chain
47 for \eqn{f_Y}{fY} may be transformed into a Markov chain for
48 \eqn{f_X}{fX}. Furthermore, these Markov chains are isomorphic
55 fY} and transforms the resulting Markov chain into a Markov chain for
115 \item{morph.final}{the final state of the Markov chain on the
H A Dmetrop.Rd7 Markov chain Monte Carlo for continuous random vector using a Metropolis
23 density of the desired equilibrium distribution of the Markov chain.
24 Its first argument is the state vector of the Markov chain. Other
34 of the Markov chain is the final state from the run recorded in
37 \item{initial}{a real vector, the initial state of the Markov chain.
58 producing a Markov chain with equilibrium distribution having a specified
89 \item{final}{final state of Markov chain.}
92 \item{time}{running time of Markov chain from \code{system.time()}.}
142 \emph{Handbook of Markov Chain Monte Carlo} (Geyer, 2011).
159 of the target distribution, a valid state of the Markov chain,
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/dports/math/openturns/openturns-1.18/python/doc/theory/data_analysis/
H A Dmetropolis_hastings.rst6 | **Markov chain.** Considering a :math:`\sigma`-algebra :math:`\cA` on
7 :math:`\Omega`, a Markov chain is a process
33 | :math:`{(X_k)}_{k\in\Nset}` is a homogeneous Markov Chain of
37 Markov Chain of transition :math:`K` on :math:`(\Omega, \cA)` with
40 - :math:`K_\nu` denotes the probability distribution of the Markov
50 | **Total variation convergence.** A Markov Chain of distribution
74 Markov Chain Monte-Carlo techniques allows to sample and integrate
83 Metropolis-Hastings algorithm produces a Markov chain
87 - the transition kernel of the Markov chain is :math:`t`-invariant;
91 - the Markov chain satisfies the *ergodic theorem*: let :math:`\phi` be
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/dports/math/R-cran-coda/coda/man/
H A Draftery.diag.Rd21 intended for use on a short pilot run of a Markov chain. The number
57 qth quantile of U. The process \eqn{Z_t} is derived from the Markov
59 a Markov chain. However, \eqn{Z_t} may behave as a Markov chain if
62 chain \eqn{Z^k_t} behave as a Markov chain. The required sample size is
79 Implementation strategies for Markov chain Monte Carlo.
84 Practical Markov Chain Monte Carlo (W.R. Gilks, D.J. Spiegelhalter
/dports/graphics/py-giddy/giddy-2.3.3/giddy/tests/
H A Dtest_mobility.py5 from ..markov import Markov
16 m = Markov(q5)
28 m = Markov(q5)
/dports/science/agrum/aGrUM-29e540d8169268e8fe5d5c69bc4b2b1290f12320/src/docs/modules/
H A Dbn.dox40 * \defgroup bn_group Markov Network
42 * \defgroup mn_inference Inference Algorithms for Markov Networks
43 * \defgroup mn_io Serialization of Markov Networks
/dports/math/R-cran-MSwM/MSwM/man/
H A DMSM-package.Rd9 …Univariate Autoregressive Markov Switching Models for Linear and Generalized Models by using the E…
30 Goldfeld, S., Quantd, R. (2005). 'A Markov model for switching Regression',Journal of Econometrics…
31 Perlin, M. (2007). 'Estimation, Simulation and Forecasting of a Markov Switching Regression', (Gene…
/dports/math/jacop/jacop-4.8.0/src/main/java/org/jacop/examples/floats/
H A DMarkov.java50 public class Markov { class
124 Markov example = new Markov(); in main()
/dports/math/octave-forge-queueing/queueing/inst/
H A Ddtmc.m23 ## @cindex Markov chain, discrete time
24 ## @cindex discrete time Markov chain
26 ## @cindex Markov chain, stationary probabilities
27 ## @cindex Markov chain, transient probabilities
29 ## Compute stationary or transient state occupancy probabilities for a discrete-time Markov chain.
33 ## discrete-time Markov chain with finite state space @math{@{1, @dots{},
/dports/archivers/lzlib/lzlib-1.12/
H A DAUTHORS4 Abraham Lempel and Jacob Ziv (for the LZ algorithm), Andrey Markov (for the
5 definition of Markov chains), G.N.N. Martin (for the definition of range
/dports/archivers/lzip/lzip-1.22/
H A DAUTHORS4 Abraham Lempel and Jacob Ziv (for the LZ algorithm), Andrey Markov (for the
5 definition of Markov chains), G.N.N. Martin (for the definition of range
/dports/science/dakota/dakota-6.13.0-release-public.src-UI/docs/KeywordMetadata/
H A Dmethod-bayes_calibration-chain_diagnostics2 Compute diagnostic metrics for Markov chain
5 While a Markov chain produced via Monte Carlo sampling eventually converges
/dports/graphics/py-giddy/giddy-2.3.3/
H A DREADME.md35 - Spatially explicit Markov methods:
36 - Spatial Markov and inference
37 - LISA Markov and inference
53 * [Markov based methods](notebooks/MarkovBasedMethods.ipynb)
54 * [Rank Markov methods](notebooks/RankMarkov.ipynb)
/dports/math/R-cran-MCMCpack/MCMCpack/inst/
H A DCITATION4 title = "{MCMCpack}: Markov Chain Monte Carlo in {R}",
16 "MCMCpack: Markov Chain Monte Carlo in R.",

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