A B C D E F G H I K L M N O P R S T U V Z misc
| markovchain-package | Easy Handling Discrete Time Markov Chains |
| absorbingStates | Various function to perform structural analysis of DTMC |
| absorbingStates-method | Markov Chain class |
| absorptionProbabilities | Absorption probabilities |
| absorptionProbabilities-method | Markov Chain class |
| aggregateStates | Aggregate a Markov chain's state space by Kullback-Leibler minimization |
| aggregateStates-method | Aggregate a Markov chain's state space by Kullback-Leibler minimization |
| assessIndependence | Test independence of consecutive states of an empirical sequence |
| assessOrder | Test the first-order Markov property of an empirical sequence |
| assessStationarity | Test the first-order Markov property of an empirical sequence |
| autoLump | Automatically aggregate a Markov chain by spectral clustering |
| autoLump-method | Automatically aggregate a Markov chain by spectral clustering |
| autoplot.markovchain | Plot a Markov chain with ggplot2 |
| birthDeath | Build a birth-death Markov chain |
| blanden | Mobility between income quartiles |
| canonicForm | Various function to perform structural analysis of DTMC |
| canonicForm-method | Markov Chain class |
| closestReversible | Closest reversible approximation of a Markov chain |
| closestReversible-method | Closest reversible approximation of a Markov chain |
| coerce-method | Markov Chain class |
| committorAB | Calculates committor of a markovchain object with respect to set A, B |
| communicatingClasses | Various function to perform structural analysis of DTMC |
| communicatingClasses-method | Markov Chain class |
| conditionalDistribution | 'conditionalDistribution' of a Markov Chain |
| conditionalDistribution-method | Markov Chain class |
| craigsendi | CD4 cells counts on HIV Infects between zero and six month |
| createSequenceMatrix | Function to fit a discrete Markov chain |
| ctmc-class | Continuous time Markov Chains class |
| ctmcFit | Function to fit a CTMC |
| dim-method | Continuous time Markov Chains class |
| dim-method | Markov Chain class |
| dim-method | Non homogeneus discrete time Markov Chains class |
| dirichletChain | Markov chain from a Dirichlet process |
| entropyRate | Entropy rate of a Markov chain |
| entropyRate-method | Entropy rate of a Markov chain |
| expectedRewards | Expected Rewards for a markovchain |
| expectedRewardsBeforeHittingA | Expected first passage Rewards for a set of states in a markovchain |
| ExpectedTime | Returns expected hitting time from state i to state j |
| firstPassage | First passage across states |
| firstPassageMultiple | function to calculate first passage probabilities |
| fitHigherOrder | Functions to fit a higher order Markov chain |
| fitHighOrderMultivarMC | Function to fit Higher Order Multivariate Markov chain |
| fitMTD | Fit a mixture transition distribution (MTD) model |
| freq2Generator | Returns a generator matrix corresponding to frequency matrix |
| fromDictionary | Represent a Markov chain as a plain R list |
| fromFile | Write or read a Markov chain to or from a file |
| fundamentalMatrix | Fundamental matrix of an absorbing Markov chain |
| gamblersRuin | Build a gambler's ruin Markov chain |
| generatorToTransitionMatrix | Function to obtain the transition matrix from the generator |
| higherOrderLogLik | Log-likelihood, deviance and information criteria of a higher order Markov chain |
| HigherOrderMarkovChain-class | Higher order Markov Chains class |
| higherOrderPredict | Next-state probabilities and simulation for higher order Markov chains |
| higherOrderSimulate | Next-state probabilities and simulation for higher order Markov chains |
| hittingProbabilities | Hitting probabilities for markovchain |
| hittingProbabilities-method | Markov Chain class |
| holson | Holson data set |
| hommc | An S4 class for representing High Order Multivariate Markovchain (HOMMC) |
| hommc-class | An S4 class for representing High Order Multivariate Markovchain (HOMMC) |
| ictmc | An S4 class for representing Imprecise Continuous Time Markovchains |
| ictmc-class | An S4 class for representing Imprecise Continuous Time Markovchains |
| identityChain | Identity Markov chain |
| impliedTimescales | Implied timescales of a Markov chain |
| impliedTimescales-method | Implied timescales of a Markov chain |
| impreciseProbabilityatT | Calculating full conditional probability using lower rate transition matrix |
| inferHyperparam | Function to infer the hyperparameters for Bayesian inference from an a priori matrix or a data set |
| initialize,ctmc_method | Continuous time Markov Chains class |
| initialize-method | Markov Chain class |
| is.accessible | Verify if a state j is reachable from state i. |
| is.accessible-method | Markov Chain class |
| is.CTMCirreducible | Check if CTMC is irreducible |
| is.irreducible | Function to check if a Markov chain is irreducible (i.e. ergodic) |
| is.irreducible-method | Markov Chain class |
| is.lumpable | Check exact lumpability of a Markov chain |
| is.lumpable-method | Check exact lumpability of a Markov chain |
| is.regular | Check if a DTMC is regular |
| is.regular-method | Markov Chain class |
| is.reversible | Check whether a Markov chain is reversible |
| is.reversible-method | Check whether a Markov chain is reversible |
| is.stochasticallyMonotone | Check if a Markov chain is stochastically monotone |
| is.stochasticallyMonotone-method | Check if a Markov chain is stochastically monotone |
| is.TimeReversible | checks if ctmc object is time reversible |
| kemenyConstant | Kemeny's constant of a Markov chain |
| kemenyConstant-method | Kemeny's constant of a Markov chain |
| kullback | Example from Kullback and Kupperman Tests for Contingency Tables |
| lazyChain | Build a lazy version of a Markov chain |
| lazyChain-method | Build a lazy version of a Markov chain |
| lump | Aggregate a Markov chain over a partition |
| lump-method | Aggregate a Markov chain over a partition |
| markovchain | Easy Handling Discrete Time Markov Chains |
| markovchain-class | Markov Chain class |
| markovchainFit | Function to fit a discrete Markov chain |
| markovchainList-class | Non homogeneus discrete time Markov Chains class |
| markovchainListFit | markovchainListFit |
| markovchainSequence | Function to generate a sequence of states from homogeneous Markov chains. |
| meanAbsorptionTime | Mean absorption time |
| meanAbsorptionTime-method | Markov Chain class |
| meanFirstPassageTime | Mean First Passage Time for irreducible Markov chains |
| meanFirstPassageTime-method | Markov Chain class |
| meanNumVisits | Mean num of visits for markovchain, starting at each state |
| meanNumVisits-method | Markov Chain class |
| meanRecurrenceTime | Mean recurrence time |
| meanRecurrenceTime-method | Markov Chain class |
| mergeWith | Merge two Markov chains by convex combination of their transition matrices |
| mergeWith-method | Merge two Markov chains by convex combination of their transition matrices |
| mixingTime | Mixing time of a Markov chain |
| mixingTime-method | Mixing time of a Markov chain |
| multinomialConfidenceIntervals | A function to compute multinomial confidence intervals of DTMC |
| name | Method to retrieve name of markovchain object |
| name-method | Method to retrieve name of markovchain object |
| name<- | Method to set name of markovchain object |
| name<--method | Method to set name of markovchain object |
| names-method | Returns the states for a Markov chain object |
| names<--method | Markov Chain class |
| noofVisitsDist | Expected fraction of the first N steps spent in each state |
| normalizedEntropyRate | Normalized entropy rate of a Markov chain |
| normalizedEntropyRate-method | Normalized entropy rate of a Markov chain |
| ones | Returns an Identity matrix |
| period | Various function to perform structural analysis of DTMC |
| plot-method | Continuous time Markov Chains class |
| plot-method | Markov Chain class |
| populationGeneticsModel | Build a population-genetics Markov chain (Moran or Wright-Fisher) |
| predict-method | Markov Chain class |
| predict-method | Non homogeneus discrete time Markov Chains class |
| predictHommc | Simulate a higher order multivariate markovchain |
| predictiveDistribution | predictiveDistribution |
| preproglucacon | Preprogluccacon DNA protein bases sequences |
| print-method | Markov Chain class |
| print-method | Non homogeneus discrete time Markov Chains class |
| priorDistribution | priorDistribution |
| probabilityatT | Calculating probability from a ctmc object |
| rain | Alofi island daily rainfall |
| randomMarkovChain | Random Markov chain |
| rctmc | rctmc |
| recurrentClasses | Various function to perform structural analysis of DTMC |
| recurrentClasses-method | Markov Chain class |
| recurrentStates | Various function to perform structural analysis of DTMC |
| recurrentStates-method | Markov Chain class |
| redistribute | Evolution of a distribution over time |
| redistribute-method | Evolution of a distribution over time |
| relaxationTime | Relaxation time of a Markov chain |
| relaxationTime-method | Relaxation time of a Markov chain |
| rmarkovchain | Function to generate a sequence of states from homogeneous or non-homogeneous Markov chains. |
| rouwenhorst | Discretize an AR(1) process into a Markov chain (Rouwenhorst's method) |
| sales | Sales Demand Sequences |
| selectOrder | Select the order of a Markov chain by information criteria |
| sensitivity | Sensitivity of the stationary distribution to a state's transition row |
| sensitivity-method | Sensitivity of the stationary distribution to a state's transition row |
| seq2freqProb | Functions to fit a higher order Markov chain |
| seq2matHigh | Functions to fit a higher order Markov chain |
| show-method | Function to display the details of hommc object |
| show-method | Markov Chain class |
| show-method | Non homogeneus discrete time Markov Chains class |
| slem | Second largest eigenvalue modulus (SLEM) of a Markov chain |
| slem-method | Second largest eigenvalue modulus (SLEM) of a Markov chain |
| sort-method | Markov Chain class |
| spectralGap | Spectral gap of a Markov chain |
| spectralGap-method | Spectral gap of a Markov chain |
| states | Defined states of a transition matrix |
| states-method | Continuous time Markov Chains class |
| states-method | Defined states of a transition matrix |
| steadyStates | Stationary states of a 'markovchain' object |
| steadyStates-method | Continuous time Markov Chains class |
| steadyStates-method | Markov Chain class |
| subchain | Restrict a Markov chain to a subset of states |
| subchain-method | Restrict a Markov chain to a subset of states |
| summary-method | Markov Chain class |
| t-method | Markov Chain class |
| tauchen | Discretize an AR(1) process into a Markov chain (Tauchen's method) |
| timeCorrelations | Time correlations and time relaxations of observed sequences |
| timeCorrelations-method | Time correlations and time relaxations of observed sequences |
| timeRelaxations | Time correlations and time relaxations of observed sequences |
| timeRelaxations-method | Time correlations and time relaxations of observed sequences |
| tm_abs | Single Year Corporate Credit Rating Transititions |
| toBoundedChain | Apply a boundary condition to a Markov chain's first and last state |
| toBoundedChain-method | Apply a boundary condition to a Markov chain's first and last state |
| toDictionary | Represent a Markov chain as a plain R list |
| toDictionary-method | Represent a Markov chain as a plain R list |
| toDot | Export the transition graph as Graphviz DOT or Mermaid text |
| toDot-method | Export the transition graph as Graphviz DOT or Mermaid text |
| toFile | Write or read a Markov chain to or from a file |
| toFile-method | Write or read a Markov chain to or from a file |
| toMermaid | Export the transition graph as Graphviz DOT or Mermaid text |
| toMermaid-method | Export the transition graph as Graphviz DOT or Mermaid text |
| toNthOrder | Return the n-step transition chain |
| topologicalEntropy | Topological entropy of a Markov chain |
| topologicalEntropy-method | Topological entropy of a Markov chain |
| transientClasses | Various function to perform structural analysis of DTMC |
| transientClasses-method | Markov Chain class |
| transientStates | Various function to perform structural analysis of DTMC |
| transientStates-method | Markov Chain class |
| transition2Generator | Return the generator matrix for a corresponding transition matrix |
| transitionProbability | Function to get the transition probabilities from initial to subsequent states. |
| transitionProbability-method | Function to get the transition probabilities from initial to subsequent states. |
| urnModel | Build an Ehrenfest urn model Markov chain |
| verifyEmpiricalToTheoretical | Test the first-order Markov property of an empirical sequence |
| verifyHomogeneity | Test the first-order Markov property of an empirical sequence |
| verifyMarkovProperty | Test the first-order Markov property of an empirical sequence |
| zeros | Matrix to create zeros |
| !=-method | Markov Chain class |
| *-method | Markov Chain class |
| .markovchainFitRcpp | Function to fit a discrete Markov chain |
| ==-method | Markov Chain class |
| [-method | Markov Chain class |
| [[-method | Non homogeneus discrete time Markov Chains class |
| ^-method | Markov Chain class |