Changes in 0.8-0

• New function: cdp(), competency deletion procedure (CDP) to reduce a set of competencies defined on a set of skills down to one of its possible reducts (drafted by Paul Doerrbecker)
• simulate.blim(): gains method argument to select Bernoulli or multinomial sampling; gains zeropad argument to complete an incomplete frequency vector with zeros
• print.blim(), print.slm(): are better at displaying stub objects
• pks is now hosted at Codeberg

Changes in 0.7-0

• BUG FIX: as.pattern(R, useNames = TRUE) works better when R consists of all-zero rows; warns when as.set = TRUE but R contains duplicated rows
• New function: predict.blim(), predict a knowledge state or state probabilities given a response pattern; works for class slm by inheritance (prompted by Paul Doerrbecker)
• blim(): more modularization and vectorization and fewer calls to apply()
• New data set: hsgeometry (Lakshminarayan, 1995, 1996)

Changes in 0.6-1

• Vignette and schoolarithm.Rd: fix typos

Changes in 0.6-0

• DESCRIPTION: suggests relations and Rgraphviz for plotting knowledge structures and precedence relations, see examples in is.subset() and in ita()
• New vignette: vignette(“EstimationStepByStep”, package = “pks”), parameter estimation methods implemented in the package
• New function: slm(), fitting and testing simple learning models
• New function: getKFringe(), outer and inner fringes of a knowledge structure
• New function: is.downgradable(), check for downgradabiliy
• conversion.R: as.pattern(…, useNames = TRUE) uses item names to represent response patterns, as.letters argument is deprecated
• ita.R: ita() gains search argument for local or global threshold search; returns precedence relation as a logical incidence matrix
• New function: is.subset(), subset relation incidence matrix
• New function: blimit(), BLIM identification analysis (adapted from Stefanutti et al., 2012)
• New data sets: fraction17 (Stefanutti and de Chiusole, 2017), subtraction13 (de Chiusole and Stefanutti, 2013)

Changes in 0.5-0

• blim(): use (if possible) matrix multiplication to compute the conditional distribution of response patterns given knowledge state; remove deprecated errequal and errtype arguments; increase default zeropad to 16
• New function: ita(), item tree analysis
• conversion.R: as.binmat() gains as.logical argument
• chess data: correct mistakes in dst1 and dst4; add raw data and replication code
• *.Rd: update references

Changes in 0.4-1

• BUG FIX: blim(…, method = “MDML”) could fail when (b)eta estimates were too close to zero (reported by Martin Losert)
• *.Rd: add DOIs to all references
• DESCRIPTION: new URL

Changes in 0.4-0

• blim(): more flexible infrastructure for setting parameter constraints; errequal and errtype arguments are now deprecated in favor of betaequal/etaequal and betafix/etafix
• New functions: anova.blim(), coef.blim(), deviance.blim()
• as.pattern(…, as.set = TRUE), as.binmat(): work in more cases including when R or N.R do not contain the empty set
• chess and probability data sets: extended examples
• NAMESPACE: import graphics

Changes in 0.3-1

• BUG FIX: delineate() could return wrong knowledge structure when skillfun had numeric itemIDs (or factor itemIDs in non-alphabetic order)
• New function: jacobian(), Jacobian matrix of a BLIM (draft version)
• delineate(): each element of classes is now a matrix; itemID is now the index of the column that holds the item indicator
• blim(): new zeropad argument; per default, an incomplete response vector is completed and padded with zeros

Changes in 0.3-0

• New function: delineate(), knowledge structure delineated by skill function
• New functions: is.forward.graded(), is.backward.graded()
• blim(): add random initial values for randinit = TRUE
• tests/sampling.R: add tests for uniform sampling
• blim(): recalculate degrees of freedom in goodness-of-fit test
• as.pattern(): add as.set argument; if TRUE return value is of class “set”
• as.binmat(): conversion from class set to matrix
• DESCRIPTION: depend on package sets

Changes in 0.2-1

• BUG FIX: simulate.blim() made incorrect predictions
• New data set: endm
• CITATION: add reference to ENDM paper

Changes in 0.2-0

• BUG FIX: likelihood and fitted values reported by blim() were incorrect
• blim(): add estimators for errequal = TRUE, speed up some computations
• New data sets: density97, matter97
• as.pattern(): add as.letters argument for a letter representation of response patterns
• CITATION: add reference to Psychoco 2012 talk

Changes in 0.1-0

• initial release on CRAN
• Function blim() for fitting and testing basic local independence models
• Extractor functions for blim objects (some work automatically by inheritance): simulate(), print(), logLik(), nobs(), resid(), fitted(), plot(), AIC(), BIC()
• Conversion functions: as.pattern() and as.binmat()
• Data sets: DoignonFalmagne7, chess, probability