lstseq.bagg {delt}R Documentation

Calculates a scale of bootstrap aggregated histograms


Calculates a scale of bootstrap aggregated histograms. The estimates in the sequence are calculated with function "eval.bagg".


lstseq.bagg(dendat, B, lstree=NULL, level = NULL, 
maxleaf = NULL, leafseq = NULL, 
minobs = NULL, seed = 1, sample = "bagg", prune = "off", 
splitscan = 0, seedf = 1, scatter = 0, src = "c", method = "loglik")


dendat n*d data matrix
B positive integer; the number of aggregated histograms
maxleaf the maximal cardinality of the partitions of the histograms in the sequence
lstree if NULL, then level set trees are not calculated
level if NULL, then shape trees are not calculated; if positive number, then it is the level of the level sets for which the shape trees are calculated
leafseq a vector giving the cardinalities of the partitions of the aggregated histograms
minobs non-negative integer; a property of aggregated histograms; splitting of a bin will be continued if the bin containes "minobs" or more observations
seed the seed for the random number generation of the random selection of the bootstrap sample
sample "bagg" or "worpl"; the bootstrapping method; "worpl" for the n/2-out-of-n without replacement; "bagg" for n-out-of-n with replacement
prune "on" or "off"; if "on", then CART-histograms will be aggregated; if "off", then greedy histograms will be aggregated
splitscan internal (how many splits will be used for random split selection)
seedf internal (seed for random split selection)
scatter internal (random perturbation of observations)
src internal ("c" or "R" code)
method "loglik" or "projec"; the empirical risk is either the log-likelihood or the L2 empirical risk


A list with components

lstseq a list of level set trees
pcfseq a list of piecewise constant functions
stseq a list of shape trees
hseq a vector of smoothing parameters corresponding to the estimates in the sequence; the smoothing parameter is the cardinality of the partitions of the aggregated histograms


Jussi Klemela

See Also




seed<-1        # seed for choosing bootstrap samples
sample="worpl" # without-replacement bootstrap
prune="on"     # we use CART-histograms
B<-2           # the number of histograms in the average





[Package delt version 0.8.0 Index]