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authorGabor Pali <pgj@FreeBSD.org>2012-12-20 02:23:04 +0000
committerGabor Pali <pgj@FreeBSD.org>2012-12-20 02:23:04 +0000
commitf6f83c9efc2c46d2970746758e2c682bb8a518ec (patch)
tree290f2ea61305744bf0f477895c56b92acaeb361f /math/hs-statistics
parentaf071cfdc1f8578bd1523b823e683074a3139a34 (diff)
downloadports-f6f83c9efc2c46d2970746758e2c682bb8a518ec.tar.gz
ports-f6f83c9efc2c46d2970746758e2c682bb8a518ec.zip
Notes
Diffstat (limited to 'math/hs-statistics')
-rw-r--r--math/hs-statistics/Makefile9
-rw-r--r--math/hs-statistics/distinfo4
-rw-r--r--math/hs-statistics/pkg-descr27
3 files changed, 18 insertions, 22 deletions
diff --git a/math/hs-statistics/Makefile b/math/hs-statistics/Makefile
index 0244f3f6cb59..6df0e00460d0 100644
--- a/math/hs-statistics/Makefile
+++ b/math/hs-statistics/Makefile
@@ -1,13 +1,8 @@
-# New ports collection makefile for: hs-statistics
-# Date created: January 03 2010
-# Whom: Giuseppe Pilichi aka Jacula Modyun <jacula@gmail.com>
-#
+# Created by: Giuseppe Pilichi aka Jacula Modyun <jacula@gmail.com>
# $FreeBSD$
-#
PORTNAME= statistics
-PORTVERSION= 0.10.1.0
-PORTREVISION= 1
+PORTVERSION= 0.10.2.0
CATEGORIES= math haskell
MAINTAINER= haskell@FreeBSD.org
diff --git a/math/hs-statistics/distinfo b/math/hs-statistics/distinfo
index 9ded011f2d1f..40dda681ee09 100644
--- a/math/hs-statistics/distinfo
+++ b/math/hs-statistics/distinfo
@@ -1,2 +1,2 @@
-SHA256 (cabal/statistics-0.10.1.0.tar.gz) = 6c29cfb8da9745debb3372897a147eb87076806f58b5b402aa4c76cea0e5d73a
-SIZE (cabal/statistics-0.10.1.0.tar.gz) = 45762
+SHA256 (cabal/statistics-0.10.2.0.tar.gz) = 3ddd3c99ffb8cf9ac44e9fd9119bb5418502404d20444b58c2aa8a12177460eb
+SIZE (cabal/statistics-0.10.2.0.tar.gz) = 58362
diff --git a/math/hs-statistics/pkg-descr b/math/hs-statistics/pkg-descr
index e90d25803559..4fcdda303a70 100644
--- a/math/hs-statistics/pkg-descr
+++ b/math/hs-statistics/pkg-descr
@@ -1,19 +1,20 @@
-This Haskell library provides a number of common functions and types
-useful in statistics. Our focus is on high performance, numerical
-robustness, and use of good algorithms. Where possible, we provide
-references to the statistical literature.
+This library provides a number of common functions and types useful in
+statistics. We focus on high performance, numerical robustness, and use
+of good algorithms. Where possible, we provide references to the
+statistical literature.
-The library's facilities can be divided into three broad categories:
+The library's facilities can be divided into four broad categories:
-Working with widely used discrete and continuous probability
-distributions. (There are dozens of exotic distributions in use; we
-focus on the most common.)
+* Working with widely used discrete and continuous probability
+ distributions. (There are dozens of exotic distributions in use; we
+ focus on the most common.)
-Computing with sample data: quantile estimation, kernel density
-estimation, bootstrap methods, and autocorrelation analysis.
+* Computing with sample data: quantile estimation, kernel density
+ estimation, histograms, bootstrap methods, significance testing, and
+ autocorrelation analysis.
-Random variate generation under several different distributions.
+* Random variate generation under several different distributions.
-Common statistical tests for significant differences between samples.
+* Common statistical tests for significant differences between samples.
-WWW: http://darcs.serpentine.com/statistics
+WWW: https://github.com/bos/statistics