Analyzes Clickstreams Based on Markov Chains
Returns All Absorbing States
Coerces a Clickstream Object to a ClickClust Object
Converts a character vector or a character list into a clickstream lis...
Coerces a Clickstream Object to a Transactions Object
Coerces a Clickstream Object to a Transactions Object
Calculates the chi-square statistic
Analyzes Clickstreams Based on Markov Chains
Performs K-Means Clustering on a List of Clickstreams
Class EvaluationResult
Shows an EvaluationResult object
Fits a List of Clickstreams to a Markov Chain
Generates a list of markov chains from a given set of clusters
Generates a Data Frame of State Frequencies for All Clickstreams in a ...
Generates an optimal set of clusters for a clickstream object based on...
Generates an optimal set of clusters for a clickstream based on consen...
Generates the optimal markov chains from a list of markov chains and c...
Plots a Heatmap
Creates a new Pattern object
Class MarkovChain
Shows a MarkovChain object
Evaluates the number of occurrences of predicted next clicks
Evaluates all next page clicks in a clickstream training data set agai...
Evaluates all next page clicks in a clickstream training data set agai...
Class Pattern
Shows a Pattern object
Plots a MarkovChain object
Concatenates two Pattern objects
Predicts the Next Click(s) of a User
Predicts the Cluster for a Given Pattern Object
Prints a ClickstreamClusters Object
Prints a Clickstreams Object
Prints the Summary of a MarkovChain Object
Generates a Sequence of Clicks
Generates a List of Clickstreams
Reads a List of Clickstreams from File
Returns All States
Prints the Summary of a MarkovChain Object
Prints a Summary of a ClickstreamCluster Object
Prints a Summary of a Clickstreams Object
Returns All Transient States
Writes a List of Clickstreams to File
A set of tools to read, analyze and write lists of click sequences on websites (i.e., clickstream). A click can be represented by a number, character or string. Clickstreams can be modeled as zero- (only computes occurrence probabilities), first- or higher-order Markov chains.