minor tweak to readme, and added extra instruction to make file

README.md

@@ -27,9 +27,9 @@ Core functions in this package are known to be compatible with versions of Octav
 
 ### Installation
 
-To install (or test) the statistics-resampling package at it's existing location in either Octave or Matlab, follow these steps: 
+To install (or test) the statistics-resampling package at a location of your choice, follow these steps: 
 
- * Download the package release from [here](https://github.com/gnu-octave/statistics-resampling/releases/). If it is a compressed file (.zip or .tar.gz), extract it's contents and move the package directory to the desired location.
+ * Download the latest package release from [here](https://github.com/gnu-octave/statistics-resampling/releases/). Extract (not just browse) the contents of the compressed file (.zip or .tar.gz), and move the package directory to the desired location.
  * Open Octave or Matlab (command prompt).
  * Change directory (cd) into the package folder. (The directory contains a file called 'make.m' and 'install.m', among others)
  * Type `make` to compile the MEX files from source (or use the precompiled binaries if available. If suitable precompiled binaries are not available for your platform, then Matlab/Octave will need access to a C++11 compiler. Note that if you skip the make step, then the package functions will still work, but some will run slower. This step is interactive so check the command window.) 

docs/function/boot.html

@@ -115,9 +115,9 @@ <h3>Demonstration 1</h3>
 <p>Produces the following output</p>
 <pre class="example">ans =
 
-   3   1   1   2   3   3   2   1   2   2   3   1   3   1   3   1   1   3   3   3
-   2   2   3   3   1   1   3   1   2   1   1   2   2   2   2   2   3   3   2   3
-   1   2   1   3   1   1   1   1   2   2   3   1   3   2   2   2   3   1   2   3</pre>
+   3   3   1   2   1   3   2   3   2   1   1   3   2   1   3   3   2   2   2   3
+   3   3   1   2   1   1   1   2   3   1   1   2   1   2   3   3   1   1   3   1
+   3   2   2   3   2   2   2   1   3   1   2   3   2   3   2   1   1   1   3   2</pre>
 </div>
 <h3>Demonstration 2</h3>
 <div class="demo">
@@ -129,9 +129,9 @@ <h3>Demonstration 2</h3>
 <p>Produces the following output</p>
 <pre class="example">ans =
 
-   3   3   1   2   3   1   2   1   2   2   1   1   3   1   2   2   3   1   1   1
-   3   3   2   3   3   2   2   1   2   2   1   2   3   1   2   3   3   2   3   1
-   3   1   1   2   3   2   3   1   1   3   3   2   3   1   2   3   1   2   1   2</pre>
+   3   3   1   3   3   2   2   1   1   2   1   1   3   3   1   3   1   2   2   1
+   2   1   2   3   3   2   3   3   1   3   1   1   3   3   2   3   1   2   2   1
+   3   3   1   2   1   2   2   1   1   2   3   2   2   1   2   2   3   2   3   1</pre>
 </div>
 <h3>Demonstration 3</h3>
 <div class="demo">

docs/function/boot1way.html

@@ -473,7 +473,7 @@ <h3>Demonstration 6</h3>
 -----------------------------------------------------------------------------
 | Comparison |     Test # |      Ref # | Difference |          t |        p |
 |------------|------------|------------|------------|------------|----------|
-|          1 |          2 |          1 |    -0.3036 |      -0.73 |     .398 |
+|          1 |          2 |          1 |    -0.9135 |      -2.67 |     .026 |*
 
 -----------------------------------------------------------------------------
 |    GROUP # |                                       GROUP label |        N |
@@ -518,7 +518,7 @@ <h3>Demonstration 7</h3>
 -----------------------------------------------------------------------------
 | Comparison |     Test # |      Ref # | Difference |          t |        p |
 |------------|------------|------------|------------|------------|----------|
-|          1 |          2 |          1 |   +0.03654 |      +0.05 |     .945 |
+|          1 |          2 |          1 |   +0.08888 |      +0.12 |     .827 |
 
 -----------------------------------------------------------------------------
 |    GROUP # |                                       GROUP label |        N |

docs/function/bootbayes.html

@@ -186,7 +186,7 @@ <h3>Demonstration 1</h3>
 
 Posterior Statistics: 
  original     bias         median       stdev       CI_lower      CI_upper
- +184.5       +0.007511    +184.5       1.296       +182.1        +187.2</pre>
+ +184.5       -0.002011    +184.5       1.331       +181.9        +187.1</pre>
 </div>
 <h3>Demonstration 2</h3>
 <div class="demo">
@@ -222,8 +222,8 @@ <h3>Demonstration 2</h3>
 
 Posterior Statistics: 
  original     bias         median       stdev       CI_lower      CI_upper
- +175.5       +0.01716     +175.5       2.380       +170.5        +180.1    
- +0.1904      -0.001915    +0.1901      0.07940     +0.02901      +0.3417</pre>
+ +175.5       -0.03629     +175.4       2.438       +170.7        +180.2    
+ +0.1904      -0.0001636   +0.1918      0.08098     +0.03791      +0.3574</pre>
 </div>
 
 <p>Package: <a href="../index.html">statistics-resampling</a></p>

docs/function/bootci.html

@@ -183,8 +183,8 @@ <h3>Demonstration 1</h3>
 <p>Produces the following output</p>
 <pre class="example">ci =
 
-   23.616
-   34.358</pre>
+   23.540
+   34.574</pre>
 </div>
 <h3>Demonstration 2</h3>
 <div class="demo">
@@ -202,8 +202,8 @@ <h3>Demonstration 2</h3>
 <p>Produces the following output</p>
 <pre class="example">ci =
 
-   23.975
-   34.269</pre>
+   23.886
+   34.390</pre>
 </div>
 <h3>Demonstration 3</h3>
 <div class="demo">
@@ -222,8 +222,8 @@ <h3>Demonstration 3</h3>
 <p>Produces the following output</p>
 <pre class="example">ci =
 
-   25.040
-   36.477</pre>
+   24.710
+   37.094</pre>
 </div>
 <h3>Demonstration 4</h3>
 <div class="demo">
@@ -239,8 +239,8 @@ <h3>Demonstration 4</h3>
 <p>Produces the following output</p>
 <pre class="example">ci =
 
-    96.629
-   235.910</pre>
+    96.788
+   237.389</pre>
 </div>
 <h3>Demonstration 5</h3>
 <div class="demo">
@@ -256,8 +256,8 @@ <h3>Demonstration 5</h3>
 <p>Produces the following output</p>
 <pre class="example">ci =
 
-   117.01
-   260.73</pre>
+   116.08
+   263.28</pre>
 </div>
 <h3>Demonstration 6</h3>
 <div class="demo">
@@ -276,8 +276,8 @@ <h3>Demonstration 6</h3>
 <p>Produces the following output</p>
 <pre class="example">ci =
 
-   108.55
-   297.71</pre>
+   116.56
+   293.82</pre>
 </div>
 <h3>Demonstration 7</h3>
 <div class="demo">
@@ -296,8 +296,8 @@ <h3>Demonstration 7</h3>
 <p>Produces the following output</p>
 <pre class="example">ci =
 
-   111.53
-   268.13</pre>
+   112.32
+   280.18</pre>
 </div>
 <h3>Demonstration 8</h3>
 <div class="demo">
@@ -317,8 +317,8 @@ <h3>Demonstration 8</h3>
 <p>Produces the following output</p>
 <pre class="example">ci =
 
-   0.5050
-   0.8633</pre>
+   0.5174
+   0.8637</pre>
 </div>
 <h3>Demonstration 9</h3>
 <div class="demo">

docs/function/bootclust.html

@@ -337,8 +337,8 @@ <h3>Demonstration 7</h3>
 
 Bootstrap Statistics: 
  original     bias         std_error    CI_lower     CI_upper  
- -0.2335      -0.001628    +0.2054      -0.5870      +0.09054   
- +0.1101      +0.007670    +0.2271      -0.2454      +0.4870</pre>
+ -0.2246      +0.03767     +0.2504      -0.6439      +0.1755    
+ -0.4531      +0.04160     +0.2805      -0.9408      -0.04681</pre>
 </div>
 <h3>Demonstration 8</h3>
 <div class="demo">
@@ -364,8 +364,8 @@ <h3>Demonstration 8</h3>
 
 Bootstrap Statistics: 
  original     bias         std_error    CI_lower     CI_upper  
- +0.1900      +0.03519     +0.2267      -0.1441      +0.5321    
- +0.04158     +0.03520     +0.3908      -0.5824      +0.6636</pre>
+ -0.06381     -0.006020    +0.2844      -0.5015      +0.4408    
+ -0.2545      -0.01749     +0.2804      -0.6349      +0.2186</pre>
 </div>
 <h3>Demonstration 9</h3>
 <div class="demo">

docs/function/bootknife.html

@@ -425,8 +425,8 @@ <h3>Demonstration 8</h3>
 
 Bootstrap Statistics: 
  original     bias         std_error    CI_lower     CI_upper  
- +0.06241     -0.01650     +0.2452      -0.3228      +0.4692    
- +0.1596      -0.0001629   +0.2018      -0.1352      +0.5346</pre>
+ +0.0004216   +0.01043     +0.1768      -0.3131      +0.2727    
+ +0.3188      -0.01964     +0.2658      -0.2203      +0.6758</pre>
 </div>
 <h3>Demonstration 9</h3>
 <div class="demo">

docs/function/bootlm.html

@@ -851,9 +851,9 @@ <h3>Demonstration 6</h3>
  ## Since the interaction term (F(1,18) = 0.42) was not significant (p > 0.1),
  ## we might rather consider the hypotheses tested using type II sums-of-
  ## squares without the interaction, which do not depend on the order and have
- ## more power respectively. This is easy to achieve with 2 predictors, by
- ## repeating the 'bootlm' commands with different predictors added last to
- ## the model (as above) but without the interaction (i.e. setting 'model',
+ ## more power respectively. This is easy to achieve with only 2 predictors,
+ ## by repeating the 'bootlm' commands with different predictors added last to
+ ## the model (as above) but without any interaction (i.e. setting 'model',
  ## 'linear'). We then take the statistics for the last main effect listed
  ## in each of the ANOVA tables - these then correspond to the ANOVA test for
  ## the respective predictor with type II sums-of-squares. For example:

docs/function/bootmode.html

@@ -148,9 +148,9 @@ <h3>Demonstration 1</h3>
 <p>Produces the following output</p>
 <pre class="example">ans = Summary of results:
 
-ans = H1 is 1 with p = 0 so reject the null hypothesisthat there is 1 mode
+ans = H1 is 1 with p = 0.0015 so reject the null hypothesisthat there is 1 mode
 
-ans = H2 is 0 with p = 0.312 so accept the null hypothesis that there are 2 modes</pre>
+ans = H2 is 0 with p = 0.329 so accept the null hypothesis that there are 2 modes</pre>
 </div>
 
 <p>Package: <a href="../index.html">statistics-resampling</a></p>

docs/function/bootstrp.html

@@ -104,58 +104,58 @@ <h3>Demonstration 1</h3>
 <p>Produces the following output</p>
 <pre class="example">bootstat =
 
-   30.385
-   26.577
-   32.962
-   26.885
-   28.962
-   27.385
-   29.538
-   28.615
-   36.269
-   29.192
-   36.192
-   35.346
-   30.923
-   31.423
-   30.231
-   25.692
-   28.577
-   27.038
-   26.269
-   31.423
-   30.154
+   27.231
+   30.462
+   26.846
    29.654
-   28.577
-   32.154
+   31.154
+   29.769
+   30.308
+   31.231
+   30.731
+   31.000
+   27.692
+   29.346
+   29.923
+   34.731
+   26.462
+   29.269
+   28.308
+   28.115
+   27.231
    28.385
-   32.615
-   24.846
-   32.269
-   25.577
-   29.615
-   26.923
+   28.462
    27.038
-   26.731
-   33.923
-   31.962
-   26.538
-   26.846
-   29.769
-   27.000
-   26.731
-   29.231
-   30.885
-   31.077
+   28.385
+   28.962
+   25.808
+   27.615
+   32.269
+   31.231
+   36.231
+   35.538
+   28.692
    30.000
-   29.115
-   31.769
-   32.423
-   30.692
-   29.231
-   31.077
-
-ans = 2.7164</pre>
+   31.615
+   29.423
+   28.846
+   26.000
+   31.231
+   35.423
+   27.615
+   28.538
+   27.385
+   30.769
+   26.462
+   25.192
+   33.769
+   27.846
+   32.462
+   31.538
+   30.885
+   29.615
+
+ans = 2.5580</pre>
 </div>
 
 <p>Package: <a href="../index.html">statistics-resampling</a></p>

docs/readme.html

@@ -59,13 +59,13 @@ <h3 id="requirements-and-dependencies">Requirements and
 Machine Learning Toolbox (in Matlab).</li>
 </ul>
 <h3 id="installation">Installation</h3>
-<p>To install (or test) the statistics-resampling package at it’s
-existing location in either Octave or Matlab, follow these steps:</p>
+<p>To install (or test) the statistics-resampling package at a location
+of your choice, follow these steps:</p>
 <ul>
-<li>Download the package release from <a
+<li>Download the latest package release from <a
 href="https://github.com/gnu-octave/statistics-resampling/releases/">here</a>.
-If it is a compressed file (.zip or .tar.gz), extract it’s contents and
-move the package directory to the desired location.</li>
+Extract (not just browse) the contents of the compressed file (.zip or
+.tar.gz), and move the package directory to the desired location.</li>
 <li>Open Octave or Matlab (command prompt).</li>
 <li>Change directory (cd) into the package folder. (The directory
 contains a file called ‘make.m’ and ‘install.m’, among others)</li>