1. Calibration and Normalization
                        1. Calibration and Normalization
aroma.light-package     Package aroma.light
averageQuantile.list    Gets the average empirical distribution
backtransformAffine.matrix
                        Reverse affine transformation
calibrateMultiscan.matrix
                        Weighted affine calibration of a multiple
                        re-scanned channel
distanceBetweenLines    Finds the shortest distance between two lines
fitIWPCA.matrix         Robust fit of linear subspace through
                        multidimensional data
iwpca.matrix            Fits an R-dimensional hyperplane using
                        iterative re-weighted PCA
likelihood.smooth.spline
                        Calculate the log likelihood of a smoothing
                        spline given the data
medianPolish.matrix     Median polish
normalizeAffine.matrix
                        Weighted affine normalization between channels
                        and arrays
normalizeAverage.matrix
                        Rescales channel vectors to get the same
                        average
normalizeCurveFit.matrix
                        Weighted curve-fit normalization between a pair
                        of channels
normalizeFragmentLength
                        Normalizes signals for PCR fragment-length
                        effects
normalizeQuantileRank.list
                        Normalizes the empirical distribution of a set
                        of samples to a target distribution
normalizeQuantileRank.matrix
                        Weighted sample quantile normalization
normalizeQuantileRank.numeric
                        Normalizes the empirical distribution of a
                        single sample to a target distribution
normalizeQuantileSpline.list
                        Normalizes the empirical distribution of a set
                        of samples to a target distribution
normalizeQuantileSpline.matrix
                        Weighted sample quantile normalization
normalizeQuantileSpline.numeric
                        Normalizes the empirical distribution of a
                        single sample to a target distribution
plotDensity.list        Plots density distributions for a set of vector
plotMvsA.matrix         Plot log-ratios vs log-intensities
plotMvsAPairs.matrix    Plot log-ratios/log-intensities for all unique
                        pairs of data vectors
plotMvsMPairs.matrix    Plot log-ratios vs log-ratios for all pairs of
                        columns
plotXYCurve.matrix      Plot the relationship between two variables as
                        a smooth curve
plotXYCurve.numeric     Plot the relationship between two variables as
                        a smooth curve
robustSmoothSpline      Robust fit of a Smoothing Spline
sampleCorrelations.matrix
                        Calculates the correlation for random pairs of
                        observations
sampleTuples            Sample tuples of elements from a set
weightedMedian          Weighted Median Value
wpca.matrix             Light-weight Weighted Principal Component
                        Analysis
