10/21/2019 · This algorithm extends the algorithm to support weighted samples. The algorithm estimates a quantile dynamically without storing samples. Instead of storing the whole sample cumulative distribution, only five points (markers) are stored. The heights of these markers are the minimum and the maximum of the samples and the current estimates of the quantiles .
So if someone is using tag:: extended_p_square_quantile for percentile(which supports multiple probabilities) then (s)he needs to give probabilities(vector/array/list) in sorted order. This isn’t the case with tag::p_square_quantile because we can give only one value(probability) in it.
extended_p_square_quantile and variants Quantile estimation using the extended P^2 algorithm for weighted and unweighted samples. By default, the calculation is linear and unweighted, but quadratic and weighted variants are also provided.
extended_ p _square extended_ p _square_ quantile and variants kurtosis max mean and variants median and variants min moment p_square_cumulative_distribution p_square_ quantile and variants peaks_over_threshold and variants pot_ quantile and variants pot_tail_mean rolling_count rolling_sum rolling_mean skewness, boost/accumulators/statistics/weighted _extended_ p _square.hpp ///// // weighted_extended_ p _square.hpp // // Copyright 2005 Daniel Egloff.
weighted variants depend on weighted_extended_ p _square unweighted variants depend on extended_ p _square. Variants. extended_ p _square_ quantile _quadratic weighted_extended_ p _square_ quantile weighted_extended_ p _square_ quantile _quadratic. Initialization Parameters. tag:: extended_ p _square:: probabilities. Accumulator Parameters, the p- quantile of a sample of n observations is pn. As the number of observations grows, the space require- ment grows and soon the exact calculation becomes infeasible due to storage considerations. To save space, experimenters often group the data in cells. However, this approach leads to many idiosyncrasies as described …
C extended_ p _square C extended_ p _square_ quantile C extended_ p _square_ quantile _quadratic C external C external C immediate_mean C immediate_mean_of_variates C immediate_mean_of_weights C immediate_rolling_mean C immediate_rolling_variance C immediate_weighted_mean C.
I am using boost::accumulators::tag::extended_ p _square_ quantile for calculating percentile. In this, I also need to feed probabilities to the accumulator so I did this m_acc = AccumulatorType(boost::accumulators::extended_ p _square_probabilities = probs) where probs is a vector containing the probabilities.
