Flow Injection Electrospray Mass Spectrometry Processing: \\ data processing, classification modelling and variable selection in metabolite fingerprinting


[Up] [Top]

Documentation for package ‘FIEmspro’ version 1.1-0

Help Pages

abr1 abr1 dataset
accest Classification Wrapper Using Customised Classifiers
accest.default Classification Wrapper Using Customised Classifiers
accest.dlist Classification Wrapper Using Customised Classifiers
accest.formula Classification Wrapper Using Customised Classifiers
dat.sel Generate Pairwise Data Set Based on Class Labels
dat.sel1 Generate Data Set List
feat.rank.re Wrapper for Resampling Based Feature Ranking
feat.rank.re.default Wrapper for Resampling Based Feature Ranking
feat.rank.re.dlist Wrapper for Resampling Based Feature Ranking
feat.rank.re.formula Wrapper for Resampling Based Feature Ranking
FIEmspro abr1 dataset
fiems_lct_main LCT Mass Binning
fiems_ltq_main LTQ Mass Binning
fs.anova Implementation of Feature Ranking Techniques
fs.auc Implementation of Feature Ranking Techniques
fs.bw Implementation of Feature Ranking Techniques
fs.kruskal Implementation of Feature Ranking Techniques
fs.mi Implementation of Feature Ranking Techniques
fs.mrpval Significance of Feature Ranking
fs.relief Implementation of Feature Ranking Techniques
fs.rf Implementation of Feature Ranking Techniques
fs.snr Implementation of Feature Ranking Techniques
fs.summary Feature Ranking Resampling Summary
fs.techniques Implementation of Feature Ranking Techniques
fs.welch Implementation of Feature Ranking Techniques
ftrank.agg Aggregation of resampling based feature ranking results
grpplot Scatter Plot by Group
hca.nlda Hierarchical Clustering for Class 'nlda'
koptimp Imputation of Low Values
mc.agg Aggregation of classification results
mc.agg.default Aggregation of classification results
mc.comp.1 Multiple Classifier Predictions Comparison
mc.comp.1.default Multiple Classifier Predictions Comparison
mc.meas.iter Summary of a predictor in mc.agg object
mc.roc Generate ROC curves from several classifiers
mc.roc.default Generate ROC curves from several classifiers
mc.summary Summary of multiple classifiers objects
mc.summary.default Summary of multiple classifiers objects
multibc Multiple Metabolomics Fingerprint Baseline Correction
nlda Linear Discriminant Analysis for High Dimensional Problems
nlda.default Linear Discriminant Analysis for High Dimensional Problems
nlda.formula Linear Discriminant Analysis for High Dimensional Problems
onebc Metabolomics Fingerprint Baseline Correction
outl.det Detection and Display Outliers
parse_freq Output Variable Frequencies in Nested Lists
parse_vec Aggregation of Vectors in Nested Lists
plot.accest Plot Method for Class 'accest'
plot.mc.roc Plot multiple ROC curves
plot.nlda Plot Method for Class 'nlda'
predict.nlda Classify Multivariate Observations by 'nlda'
preproc Data Tranformation Wrapper
print.accest Classification Wrapper Using Customised Classifiers
print.feat.rank.re Wrapper for Resampling Based Feature Ranking
print.mc.agg Aggregation of classification results
print.mc.comp.1 Multiple Classifier Predictions Comparison
print.mc.summary Summary of multiple classifiers objects
print.nlda Linear Discriminant Analysis for High Dimensional Problems
print.summary.accest Classification Wrapper Using Customised Classifiers
print.summary.nlda Linear Discriminant Analysis for High Dimensional Problems
summ.ftrank Summarise multiple resampling based feature ranking outputs
summary.accest Classification Wrapper Using Customised Classifiers
summary.nlda Linear Discriminant Analysis for High Dimensional Problems
ticstats Compute and Display Total Ion Count (TIC) statistics
tidy.ftrank Tidy up multiple resampling based ranking results.
trainind Generation of Training Samples Indices
trainind.cv Constrained Generation of Training Samples Indices
valipars Generate Control Parameters For Validation / Resampling