Source: t-digest Section: java Priority: optional Maintainer: Debian Java Maintainers Uploaders: tony mancill Build-Depends: debhelper (>= 11), default-jdk, maven-debian-helper (>= 1.5) Build-Depends-Indep: libmaven-javadoc-plugin-java, default-jdk-doc Standards-Version: 4.3.0 Vcs-Git: https://salsa.debian.org/java-team/t-digest.git Vcs-Browser: https://salsa.debian.org/java-team/t-digest Homepage: https://github.com/tdunning/t-digest Package: libt-digest-java Architecture: all Depends: ${misc:Depends}, ${maven:Depends} Suggests: ${maven:OptionalDepends}, libt-digest-java-doc Description: Data structure for quantiles and related rank statistics The t-digest construction algorithm uses a variant of 1-dimensional k-means clustering to product a data structure that is related to the Q-digest. This t-digest data structure can be used to estimate quantiles or compute other rank statistics. The advantage of the t-digest over the Q-digest is that the t-digest can handle floating point values while the Q-digest is limited to integers. With small changes, the t-digest can handle any values from any ordered set that has something akin to a mean. The accuracy of quantile estimates produced by t-digests can be orders of magnitude more accurate than those produced by Q-digests in spite of the fact that t-digests are more compact when stored on disk. Package: libt-digest-java-doc Architecture: all Section: doc Depends: ${misc:Depends}, ${maven:DocDepends} Recommends: ${maven:DocOptionalDepends} Suggests: libt-digest-java Description: Documentation for libt-digest-java Data structure which allows accurate estimation of quantiles and related rank statistics . This package contains the API documentation of libt-digest-java.