Contains a set of utilities for building and testing statistical models (linear, logistic,ordinal or COX) for Computer Aided Diagnosis/Prognosis applications. Utilities include data adjustment, univariate analysis, model building, model-validation, longitudinal analysis, reporting and visualization.

Changes from FRESA.CAD 3.0.1 to FRESA.CAD version 3.1.0

```
Enhancements:
BSWiMS now can do ordinal regression
New functions for cross-validation regression/ordinal and binary classification methods
-randomCV
-RegresionBenchmark
-BinaryBenchmark
-OrdinalBenchmark
-predictStats
Functions for filtering features
-univariate_Logit
-univariate_residual
-univariate_tstudent
-univariate_Wilcoxon
-univariate_correlation
-classic mRMR
Plots:
-barPlotCiError
Interface Changes:
forward selections now requires that the user specify the original number of features for FDR adjustment.
FDR BH p-value correction added into the forward selection algorithms: ForwardSelection.Model.Bin.R and ForwardSelection.Model.Res.R
The adjusted p-value is used at each bootstrap to detect which features can be added to the forward models
Code Changes:
Forward selection now is faster for highly dimensional data sets (n>200 features)
Before finding the optimal feature to add, it ranks features according to the correlation to the current residual.
Other:
Vignettes added
OPENMP removed from Makevars
```

Changes from FRESA.CAD 3.0.0 to FRESA.CAD version 3.0.1

```
outcheck.txt was removed from the package.
```

Changes from FRESA.CAD 2.2.1 to FRESA.CAD version 3.0.0

```
FRESA.CAD now has the ability to create gene signatures and a simple interface for BSWiMS model generation.
The BSWiMS modeling returns a bagged model after finding a set of candidate models.
Enhancements:
New functions:
-BSWiMS function added
-getSignature function added
-eB:SWIMS functionality
-nearestNeighborImpute for data imputation
Software improvements:
-c++ source code reviewed for efficiency
-bootstrappValidation Variable elimination functions rewritten. Now they attempt to provide models at optimal performance.
-CrossValidation now is using a reduced data set.
Interface Changes:
medianPredict now is called ensemblePredict
Loop_threshold removed from FRESA.Model and cross-validation
fast=FALSE in modelFitting changed to fitFRESA=TRUE
Bugs:
Several bugs corrected.
CRAN:
Removed register from c++ code
```

Changes from FRESA.CAD 2.2.0 to FRESA.CAD version 2.2.1

```
Enhancements:
meatMaps(...)
Class color bar next to categories
UnivariateRankVariables()
Now has the option to include only tail analysis
Now it store the beta coefficient
rankInverseNormalDataFrame(...,strata=NA)
Now you can specify a conditional ranking by specifying the strata
Now we can predict results from LASSO by retuning the filtered features
LASSO formulas now reported.
Bugs:
Univariate analysis of improved residuals fixed
several minors bug fixed.
```

Changes from FRESA.CAD 2.1.3 to FRESA.CAD version 2.2.0

```
FRESA.CAD expanded its capabilities.
Now it provided Bagged models and ensemble analysis from the list of formulas created by:
+ ForwardSelections.Models.Bin
+ ForwardSelections.Models.Res
+ crossValidationFeatureSelection.Bin
+ crossValidationFeatureSelection.Res
The baggedModel function bag the formula coefficients and creates a single model from the list of formulas.
The plotModels.ROC ensemble the model predictions and creates an unique test evaluation of the ensembled models.
-Added function:
baggedModel.R function for coefficient bagging, and variable frequency analysis
-Enhanced function:
plotModels.ROC.R: This function provides ensemble predictions and confusion analysis table
heatMaps.R can accept a list of five colors for its display
-c++ code revised and minor bugs corrected.
-r code revised and bugs corrected.
```

Changes from FRESA.CAD 2.0.1 to FRESA.CAD version 2.1.3

```
FRESA.CAD suffered mayor changes from the previous version.
The new version is more effective in handling memory, some functions and outputs
were renamed.
-Function Name Changes
+backVarElimination to backVarElimination_Bin
+backVarNeRiElimination to backVarElimination_Res
+bootstrapValidation to bootstrapValidation_Bin
+bootstrapNeRiValidation to bootstrapValidation_Res
+bootstrapVarElimination to bootstrapVarEliminiation_Bin
+bootstrapVarNeRiElimination to bootstrapVarEliminiation_Res
+crossValidationFeatureSelection to +crossValidationFeatureSelection_Bin
+crossValidationNeRiFeatureSelection to +crossValidationFeatureSelection_Res
+ReclassificationFRESA.Model to ForwardModel_Res
+NeRIBasedFRESA.Model to ForwardModel_Res
+getVarReclassification to getVar_Bin
+getVarNeRI to getVar_Res
+plot.bootstrapValidation to plot.bootstrapValidation_Bin
+plot.bootstrapValidationNeRI to plot.bootstrapValidation_Res
+updateModel to updateModel_Bin
+updateNeRImodel to updateModel_Res
-Renamed Outputs
Model created form forward models followed by back elimination renamed BSWiMS models
enet renamed LASSO
-Enhancements
+cross-validation now stores ID of sampled subject as well as training fits
+cross-validation now reports the ensemble estimations
+Update model added model-size-based Benjaminiâ€“Hochberg procedure (BH)
+Timeseriesanalysis changed the presentation of p values to t values
+beforeFSC formulas produced before the BH correction
+Minor bugs:
+report equivalent variables for regression models
+removed first term of formula list of cross-validation process
+removed exact wilcoxon test
+other minor bugs
-Code reviews
+NAN were replaced by nan("") c++ function
+cpp code revision to remove abs and sign warnings
+median predict revised to work with the new structure of the formula list provided by cross-validation
+speedglm removed from dependencies
```

Changes from FRESA.CAD 2.0.1 to FRESA.CAD version 2.0.2 +variable _X from code was renamed _xmat

Changes from FRESA.CAD 2.0 to FRESA.CAD version 2.0.1

C++ code was reviewed to met section 1.6.4 "Portable C and C++ code" of "Writing R Extensions" manual. Dependencies to c-standard libraries removed and round(x) changed to R::fprec(x,0).

Changes from FRESA.CAD 1.0 to FRESA.CAD version 2.0

```
+ Added c++ libraries to speed-up feature selection.
The c++ libraries functions were written using ARMADILLO and openMP.
+ FRESAcommons.cpp : Auxiliary functions with ARMADILLO implementations of COX, logit and linear fitting
+ binaryFeatureSelectionCpp.cpp: Main functions for bootstrapping, selection and estimation of
features confidence intervals for binary classification models.
+ regresionFeatureSelectionCpp.cpp: Main functions for bootstrapping, selection and estimation of
linear models coefficients.
+ rankInverseNormalCpp.cpp: Function to standardize features based on their ranking
+ Improvements and bug-fix across the FRESA.CAD package to deal with exceptions and zero size models.
+ Interface changes:
*in bootstrapValidation_Bin(...,dataframe,...)
"dataframe" argument renamed "data"
*in bootstrapValidation_Res(...,dataframe,...)
"dataframe" argument renamed "data"
*in bootVarNeRIElimination(...,bootLoops=64,bootFraction=1.0,...)
"bootLoops" and "bootFraction" arguments renamed "loops" and "fraction" respectively.
*in crossValidationFeatureSelection_Bin(...,dataframe,...,backBootLoops,...,bootEstimations,...)
"dataframe", "backBootLoops" and "bootEstimations" arguments renamed
"data", "elimination.bootstrap.steps" and "bootstrap.steps" respectively
*in crossValidationFeatureSelection_Res(...,dataframe,...,backBootLoops,...)
"dataframe" and "backBootLoops" arguments renamed
"data" and "elimination.bootstrap.steps" respectively
*in featureAdjustment(...,dataframe,...)
"dataframe" argument renamed "data"
*FRESA.Model(...,k,...)
"k" argument renamed "nk"
*getKNNpredictionFromFormula(modelFormula,...,k,...)
"modelFormula" and "k" arguments renamed "model.formula" and "nk" respectively
*getVar.Res(...,dataframe,...)
"dataframe" argument renamed "data"
*getVar.Bin(...,dataframe,...)
"dataframe" argument renamed "data"
*heatMaps(...,dataframe,...)
"dataframe" argument renamed "data"
*listTopCorrelatedVariables(...,dataframe,...)
"dataframe" argument renamed "data"
*ensemblePredict(...,newdata,...,k,...)
"newdata" and "k" arguments renamed "testdata" and "nk" respectively
*modelFitting(model,dataframe,...)
"model" and "dataframe" arguments renamed "mode.formula" and "data" respectively
*ForwardSelection.Model.Res(...,dataframe,...)
"dataframe" argument renamed "data"
*predictForFresa(...,newdata,type,...) ->
"newdata" and "type" arguments renamed "testdata" and "predictType" respectively
*rankInverseNormalDataFrame(varList, dataframe,..)
"varList" and "dataframe" arguments renamed "variableList" and "data" respectively
*ForwardSelection.Model.Bin(...,dataframe,...)
"dataframe" argument renamed "data"
*reportEquivalentVariables(...,dataframe,...)
"dataframe" argument renamed "data"
*residualForFRESA(...,newdata,...)
"newdata" argument renamed "testData"
*timeSerieAnalysis(...,dataframe,...)
"dataframe" argument renamed "data"
*uniRankVar(...,dataframe,...,FitType,..)
"dataframe" and "FitType" arguments renamed "data" and "type" respectively
*univariateRankVariables(...,dataframe,...,FitType,..)
"dataframe" and "FitType" arguments renamed "data" and "type" respectively
*updateModel.Bin(...,dataframe,...)
"dataframe" argument renamed "data"
*updateModel.Res(...,dataframe,...)
"dataframe" argument renamed "data"
```