stats.rdoc in gsl-1.16.0.6

- old
+ new

@@ -1,19 +1,19 @@
 #
 # = Statistics
-# 1. {Mean, Standard Deviation and Variance}[link:files/rdoc/stats_rdoc.html#1]
-# 1. {Absolute deviation}[link:files/rdoc/stats_rdoc.html#2]
-# 1. {Higher moments (skewness and kurtosis)}[link:files/rdoc/stats_rdoc.html#3]
-# 1. {Autocorrelation}[link:files/rdoc/stats_rdoc.html#4]
-# 1. {Covariance}[link:files/rdoc/stats_rdoc.html#5]
-# 1. {Correlation}[link:files/rdoc/stats_rdoc.html#6]
-# 1. {Weighted samples}[link:files/rdoc/stats_rdoc.html#7]
-# 1. {Maximum and minimum values}[link:files/rdoc/stats_rdoc.html#8]
-# 1. {Median and percentiles}[link:files/rdoc/stats_rdoc.html#9]
-# 1. {Examples}[link:files/rdoc/stats_rdoc.html#10]
+# 1. {Mean, Standard Deviation and Variance}[link:rdoc/stats_rdoc.html#label-Mean%2C+Standard+Deviation+and+Variance]
+# 1. {Absolute deviation}[link:rdoc/stats_rdoc.html#label-Absolute+deviation]
+# 1. {Higher moments (skewness and kurtosis)}[link:rdoc/stats_rdoc.html#label-Higher+moments+%28skewness+and+kurtosis%29]
+# 1. {Autocorrelation}[link:rdoc/stats_rdoc.html#label-Autocorrelation]
+# 1. {Covariance}[link:rdoc/stats_rdoc.html#label-Covariance]
+# 1. {Correlation}[link:rdoc/stats_rdoc.html#label-Correlation]
+# 1. {Weighted samples}[link:rdoc/stats_rdoc.html#label-Weighted+samples]
+# 1. {Maximum and minimum values}[link:rdoc/stats_rdoc.html#label-Maximum+and+Minimum+values]
+# 1. {Median and percentiles}[link:rdoc/stats_rdoc.html#label-Median+and+Percentiles]
+# 1. {Examples}[link:rdoc/stats_rdoc.html#label-Example]
 #
-# == {}[link:index.html"name="1] Mean, Standard Deviation and Variance
+# == Mean, Standard Deviation and Variance
 #
 # ---
 # * GSL::Stats::mean(v)
 # * GSL::Vector#mean
 #
@@ -21,11 +21,11 @@
 #
 #   * Ex:
 #        >> require("gsl")
 #        => true
 #        >> v = Vector[1..7]
-#        => GSL::Vector: 
+#        => GSL::Vector:
 #        [ 1.000e+00 2.000e+00 3.000e+00 4.000e+00 5.000e+00 6.000e+00 7.000e+00 ]
 #        >> v.mean
 #        => 4.0
 #        >> Stats::mean(v)
 #        => 4.0
@@ -41,94 +41,94 @@
 #   Returns the total sum of squares about <tt>mean</tt>.
 #   (Requires GSL 1.11)
 #
 # ---
 # * GSL::Stats::variance_m(v[, mean])
-# * GSL::Vector#variance_m([mean])
+# * \GSL::Vector#variance_m([mean])
 #
 #   Variance of <tt>v</tt> relative to the given value of <tt>mean</tt>.
 #
 # ---
 # * GSL::Stats::sd(v[, mean])
-# * GSL::Vector#sd([mean])
+# * \GSL::Vector#sd([mean])
 #
 #   Standard deviation.
 #
 # ---
 # * GSL::Stats::tss(v[, mean])
-# * GSL::Vector#tss([mean])
+# * \GSL::Vector#tss([mean])
 #
-#   (GSL-1.11 or later) These methods return the total sum of squares (TSS) of data about the mean.	
+#   (GSL-1.11 or later) These methods return the total sum of squares (TSS) of data about the mean.
 #
 # ---
 # * GSL::Stats::variance_with_fixed_mean(v, mean)
 # * GSL::Vector#variance_with_fixed_mean(mean)
 #
-#   Unbiased estimate of the variance of <tt>v</tt> when the population mean 
+#   Unbiased estimate of the variance of <tt>v</tt> when the population mean
 #   <tt>mean</tt> of the underlying distribution is known <tt>a priori</tt>.
 #
 # ---
 # * GSL::Stats::variance_with_fixed_mean(v, mean)
 # * GSL::Vector#variance_with_fixed_mean(mean)
 # * GSL::Stats::sd_with_fixed_mean(v, mean)
 # * GSL::Vector#sd_with_fixed_mean(mean)
 #
-#   Unbiased estimate of the variance of <tt>v</tt> when the population mean 
+#   Unbiased estimate of the variance of <tt>v</tt> when the population mean
 #   <tt>mean</tt> of the underlying distribution is known <tt>a priori</tt>.
 #
-# == {}[link:index.html"name="2] Absolute deviation 
+# == Absolute deviation
 # ---
 # * GSL::Stats::absdev(v[, mean])
-# * GSL::Vector#absdev([mean])
+# * \GSL::Vector#absdev([mean])
 #
 #   Compute the absolute deviation (from the mean <tt>mean</tt> if given).
 #
-# == {}[link:index.html"name="3] Higher moments (skewness and kurtosis) 
+# == Higher moments (skewness and kurtosis)
 #
 # ---
 # * GSL::Stats::skew(v[, mean, sd])
-# * GSL::Vector#skew([mean, sd])
+# * \GSL::Vector#skew([mean, sd])
 #
 #   Skewness
 #
 # ---
 # * GSL::Stats::kurtosis(v[, mean, sd])
-# * GSL::Vector#kurtosis([mean, sd])
+# * \GSL::Vector#kurtosis([mean, sd])
 #
 #   Kurtosis
 #
-# == {}[link:index.html"name="4] Autocorrelation
+# == Autocorrelation
 # ---
 # * GSL::Stats::lag1_autocorrelation(v[, mean])
-# * GSL::Vector#lag1_autocorrelation([mean])
+# * \GSL::Vector#lag1_autocorrelation([mean])
 #
 #   The lag-1 autocorrelation
 #
-# == {}[link:index.html"name="5] Covariance
+# == Covariance
 # ---
 # * GSL::Stats::covariance(v1, v2)
 # * GSL::Stats::covariance_m(v1, v2, mean1, mean2)
 #
 #   Covariance of vectors <tt>v1, v2</tt>.
 #
-# == {}[link:index.html"name="6] Correlation
+# == Correlation
 # ---
 # * GSL::Stats::correlation(v1, v2)
 #
 #   This efficiently computes the Pearson correlation coefficient between the vectors <tt>v1, v2</tt>. (>= GSL-1.10)
 #
-# == {}[link:index.html"name="7] Weighted samples
+# == Weighted samples
 # ---
 # * GSL::Vector#wmean(w)
 # * GSL::Vector#wvariance(w)
 # * GSL::Vector#wsd(w)
 # * GSL::Vector#wabsdev(w)
 # * GSL::Vector#wskew(w)
 # * GSL::Vector#wkurtosis(w)
 #
 #
-# == {}[link:index.html"name="8] Maximum and Minimum values 
+# == Maximum and Minimum values
 # ---
 # * GSL::Stats::max(data)
 # * GSL::Vector#max
 #
 #   Return the maximum value in data.
@@ -147,53 +147,53 @@
 #
 # ---
 # * GSL::Stats::max_index(data)
 # * GSL::Vector#max_index
 #
-#   Return the index of the maximum value in <tt>data</tt>. 
-#   The maximum value is defined as the value of the element x_i 
-#   which satisfies x_i >= x_j for all j. 
-#   When there are several equal maximum elements then the first one is chosen. 
+#   Return the index of the maximum value in <tt>data</tt>.
+#   The maximum value is defined as the value of the element x_i
+#   which satisfies x_i >= x_j for all j.
+#   When there are several equal maximum elements then the first one is chosen.
 # ---
 # * GSL::Stats::min_index(data)
 # * GSL::Vector#min_index
 #
-#   Returns the index of the minimum value in <tt>data</tt>. 
-#   The minimum value is defined as the value of the element x_i 
-#   which satisfies x_i >= x_j for all j. 
-#   When there are several equal minimum elements then the first one is 
-#   chosen. 
+#   Returns the index of the minimum value in <tt>data</tt>.
+#   The minimum value is defined as the value of the element x_i
+#   which satisfies x_i >= x_j for all j.
+#   When there are several equal minimum elements then the first one is
+#   chosen.
 #
 # ---
 # * GSL::Stats::minmax_index(data)
 # * GSL::Vector#minmax_index
 #
-#   Return the indexes of the minimum and maximum values in <tt>data</tt> 
-#   in a single pass. 
+#   Return the indexes of the minimum and maximum values in <tt>data</tt>
+#   in a single pass.
 #
 #
-# == {}[link:index.html"name="9] Median and Percentiles 
+# == Median and Percentiles
 #
 # ---
 # * GSL::Stats::median_from_sorted_data(v)
 # * GSL::Vector#median_from_sorted_data
 #
-#   Return the median value. The elements of the data must be 
-#   in ascending numerical order. There are no checks to see whether 
-#   the data are sorted, so the method <tt>GSL::Vector#sort</tt> 
+#   Return the median value. The elements of the data must be
+#   in ascending numerical order. There are no checks to see whether
+#   the data are sorted, so the method <tt>GSL::Vector#sort</tt>
 #   should always be used first.
 #
 # ---
 # * GSL::Stats::quantile_from_sorted_data(v)
 # * GSL::Vector#quantile_from_sorted_data
 #
-#   Return the quantile value. The elements of the data must be 
-#   in ascending numerical order. There are no checks to see whether 
-#   the data are sorted, so the method <tt>GSL::Vector#sort</tt> 
+#   Return the quantile value. The elements of the data must be
+#   in ascending numerical order. There are no checks to see whether
+#   the data are sorted, so the method <tt>GSL::Vector#sort</tt>
 #   should always be used first.
 #
-# == {}[link:index.html"name="10] Example
+# == Example
 #
 #      #!/usr/bin/env ruby
 #      require 'gsl'
 #
 #      ary =  [17.2, 18.1, 16.5, 18.3, 12.6]
@@ -209,11 +209,11 @@
 #      printf("The sample mean is %g\n", mean);
 #      printf("The estimated variance is %g\n", variance);
 #      printf("The largest value is %g\n", largest);
 #      printf("The smallest value is %g\n", smallest);
 #
-# {prev}[link:files/rdoc/randist_rdoc.html]
-# {next}[link:files/rdoc/hist_rdoc.html]
+# {prev}[link:rdoc/randist_rdoc.html]
+# {next}[link:rdoc/hist_rdoc.html]
 #
-# {Reference index}[link:files/rdoc/ref_rdoc.html]
-# {top}[link:files/rdoc/index_rdoc.html]
+# {Reference index}[link:rdoc/ref_rdoc.html]
+# {top}[link:index.html]
 #