class TKDE: public TNamed

Class constructor

Class destructor

 Template's constructor surrogate

Sets User defined construction options

 Sets User defined drawing options

 Gets User defined KDE construction options

 Sets missing construction options to default ones

 Sets User global options

 Sets User option for the choice of kernel estimator

 Sets User option for fixed or adaptive iteration

 Sets User option for mirroring the data

 Sets User option for binning the weights

 Sets User option for number of bins

 Sets User option for the minimum number of events for allowing automatic binning

 Factor which can be used to tune the smoothing.
 It is used as multiplicative factor for the fixed and adaptive bandwidth.
 A value < 1 will reproduce better the tails but oversmooth the peak
 while a factor > 1 will overestimate the tail

 Sets minimum range value and maximum range value

 Sets User option for using binned weights

 Sets the mirroring

 Sets the data events input sample or bin centres for binned option and computes basic estimators

 re-initialize when new data have been filled in TKDE
 re-compute kernel quantities and mean and sigma

 Mirrors the data

 Computes input data's mean

 Computes input data's sigma

 Sets the kernel density estimator

 Sets kernel estimator

 Sets the canonical bandwidths according to the kernel type

 Sets the kernel sigmas2 according to the kernel type

 Returns the PDF estimate as a function sampled in npx between xMin and xMax
 the KDE is not re-normalized to the xMin/xMax range.
 The user manages the returned function
 For getting a non-sampled TF1, one can create a TF1 directly from the TKDE by doing
 TF1 * f1  = new TF1("f1",kde,xMin,xMax,0);

 Returns the PDF upper estimate (upper confidence interval limit)

 Returns the PDF lower estimate (lower confidence interval limit)

 Returns the PDF estimate bias

 Fills data member with User input data event for the unbinned option

 The class's unary function: returns the kernel density estimate

 The class's unary function: returns the kernel density estimate

 return the mean of the data

 return the standard deviation  of the data

 Returns the Root Asymptotic Mean Integrated Squared Error according to Silverman's rule of thumb with assumed Gaussian density

 Returns the bins' centres from the data for using with the binned option

 Returns the bins' count from the data for using with the binned option

 Draws either the KDE functions or its errors
 Possible options:
                    ""  (default) - draw just the kde
                    "same" draw on top of existing pad
                    "Errors" draw a TGraphErrors with the point and errors
                    "confidenceinterval" draw KDE + conf interval functions (default is 95%)
                    "confidenceinterval@0.90" draw KDE + conf interval functions at 90%
                      Extra options can be passed in opt for drawing the TF1 or the TGraph

NOTE:  The functions GetDrawnFunction(), GetDrawnUpperFunction(), GetDrawnLowerFunction()
  and GetGraphWithErrors() return the corresponding drawn objects (which are maneged by the TKDE)
 They can be used to changes style, color, etc...

 Draws a TGraphErrors for the KDE errors

 Draws the KDE and its confidence interval

 Returns the bandwidth for the non adaptive KDE

 Returns the bandwidths for the adaptive KDE

 Returns the indices (bins) for the binned weights

 Returns the pointwise upper estimated density

 Returns the pointwise lower estimated density

 Returns the pointwise approximate estimated density bias

 Returns the pointwise sigma of estimated density

 Checks if kernel has unit integral, mu = 0 and positive finite sigma conditions

 Computes the kernel's L2 norm

 Computes the kernel's sigma squared

 Computes the kernel's mu

 Computes the kernel's integral which ought to be unity

 Computes the inter-quartile range from the data

 Computes the user's input kernel function canonical bandwidth

 Computes the user's input kernel function sigma2

Returns the estimated density

 Returns the upper estimated density

 Returns the upper estimated density

 Returns the approximate bias

 get the drawn object to chanage settings
 These objects are managed by TKDE and should not be deleted by the user

 Returns the kernel evaluation at x

 Returns the kernel evaluation at x

 Returns the kernel evaluation at x