Tools for creating conditional probability tables


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Documentation for package ‘CPTtools’ version 0.7-2

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CPTtools-package Tools for creating conditional probability tables
ACED Data from ACED field trial
ACED.items Data from ACED field trial
ACED.prePost Data from ACED field trial
ACED.scores Data from ACED field trial
ACED.skillNames Data from ACED field trial
areaProbs Translates between normal and categorical probabilities
as.CPA Representation of a conditional probability table as an array.
as.CPF Representation of a conditional probability table as a data frame.
barchart.CPF This function produces a plot of a conditional probability frame.
betaci Credibility intervals for a proportion based on beta distribution
build2FactorTab Builds probability tables from Scored Bayes net output.
buildFactorTab Builds probability tables from Scored Bayes net output.
buildMarginTab Builds probability tables from Scored Bayes net output.
buildParentList Builds a list of parents of nodes in a graph
buildRegressions Creates a series of regressions from a covariance matrix
buildRegressionTables Builds conditional probability tables from regressions
calcDDFrame Calculates DiBello-Dirichlet model probability and parameter tables
calcDDTable Calculates DiBello-Dirichlet model probability and parameter tables
calcDNFrame Creates the probability table for DiBello-Normal distribution
calcDNllike Calculates the log-likelihood for data from a DiBello-Samejima (Normal) distribution
calcDNTable Creates the probability table for DiBello-Normal distribution
calcDPCFrame Creates the probability table for the discrete partial credit model
calcDPCTable Creates the probability table for the discrete partial credit model
calcDSFrame Creates the probability table for DiBello-Samejima distribution
calcDSllike Calculates the log-likelihood for data from a DiBello-Samejima (Normal) distribution
calcDSTable Creates the probability table for DiBello-Samejima distribution
calcNoisyAndFrame Calculate the conditional probability table for a Noisy-And or Noisy-Min distribution
calcNoisyAndTable Calculate the conditional probability table for a Noisy-And or Noisy-Min distribution
calcNoisyOrFrame Calculate the conditional probability table for a Noisy-Or distribution
calcNoisyOrTable Calculate the conditional probability table for a Noisy-Or distribution
ciTest Tests for conditional independence between two variables given a third
colorspread Produces an ordered palate of colours with the same hue.
compareBars Produces comparison stacked bar charts for two sets of groups
compareBars2 Produces comparison stacked bar charts for two sets of groups
Compensatory DiBello-Samejima combination function
Conjunctive DiBello-Samejima combination function
CPA Representation of a conditional probability table as an array.
CPF Representation of a conditional probability table as a data frame.
CPTtools Tools for creating conditional probability tables
dataTable Constructs a table of counts from a set of discrete observations.
Disjunctive DiBello-Samejima combination function
EAPBal Produces a graphical balance sheet for EAP or other univarate statistics.
effectiveThetas Assigns effective theta levels for categorical variable
eThetaFrame Constructs a data frame showing the effective thetas for each parent combination.
factorPart Splits a mixed data frame into a numeric matrix and a factor part.
fcKappa Functions for measuring rater agreement.
getOffsetRules Distinguishes Offset from ordinary rules.
getTableParents Gets meta data about a conditional probability table.
getTableStates Gets meta data about a conditional probability table.
gkLambda Functions for measuring rater agreement.
gradedResponse A link function based on Samejima's graded response
is.CPA Representation of a conditional probability table as an array.
is.CPF Representation of a conditional probability table as a data frame.
isDecreasing Tests to see if a sequence is ascending or descending
isIncreasing Tests to see if a sequence is ascending or descending
isMonotonic Tests to see if a sequence is ascending or descending
isNondecreasing Tests to see if a sequence is ascending or descending
isNonincreasing Tests to see if a sequence is ascending or descending
isOffsetRule Distinguishes Offset from ordinary rules.
localDepTest Tests for conditional independence between two variables given a third
mapDPC Finds an MAP estimate for a discrete partial credit CPT
marginTab Builds probability tables from Scored Bayes net output.
MathGrades Grades on 5 mathematics tests from Mardia, Kent and Bibby
mcSearch Orders variables using Maximum Cardinality search
mutualInformation Calculates Mutual Information for a two-way table.
normalize Normalizes a conditional probability table.
normalize.array Normalizes a conditional probability table.
normalize.CPA Normalizes a conditional probability table.
normalize.CPF Normalizes a conditional probability table.
normalize.data.frame Normalizes a conditional probability table.
normalize.default Normalizes a conditional probability table.
normalize.matrix Normalizes a conditional probability table.
normalizeTable Rescales the numeric part of the table
normalLink Link function using a normal regression.
numericPart Splits a mixed data frame into a numeric matrix and a factor part.
OCP Observable Characteristic Plot
OCP2 Observable Characteristic Plot
OffsetConjunctive Conjunctive combination function with one difficulty per parent.
OffsetDisjunctive Conjunctive combination function with one difficulty per parent.
parseProbVec Parses Probability Vector Strings
parseProbVecRow Parses Probability Vector Strings
partialCredit A link function based on the generalized partial credit model
proflevelci Produce cumulative sum credibility intervals
pvecToCutpoints Translates between normal and categorical probabilities
pvecToMidpoints Translates between normal and categorical probabilities
readHistory Reads a file of histories of marginal distributions.
rescaleTable Rescales the numeric part of the table
scaleMatrix Scales a matrix to have a unit diagonal
scaleTable Scales a table according to the Sum and Scale column.
setOffsetRules Distinguishes Offset from ordinary rules.
stackedBarplot Produces a hanging barplot
stackedBars Produces a stacked, staggered barplot
structMatrix Finds graphical structure from a covariance matrix
woeBal Weight of Evidence Balance Sheet
woeHist Creates weights of evidence from a history matrix.